Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
126 tokens/sec
GPT-4o
47 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Efficient k-step Weighted Reachability Query Processing Algorithms (2403.13181v2)

Published 19 Mar 2024 in cs.DB

Abstract: Given a data graph G, a source vertex u and a target vertex v of a reachability query, the reachability query is used to answer whether there exists a path from u to v in G. Reachability query processing is one of the fundamental operations in graph data management, which is widely used in biological networks, communication networks, and social networks to assist data analysis. The data graphs in practical applications usually contain information such as quantization weights associated with the structural relationships, in addition to the structural relationships between vertices. Thus, in addition to the traditional reachability relationships, users may want to further understand whether such reachability relationships satisfy specific constraints. In this paper, we study the problem of efficiently processing k -step reachability queries with weighted constraints in weighted graphs. The k -step weighted reachability query questions are used to answer the question of whether there exists a path from a source vertex u to a goal vertex v in a given weighted graph. If it exists, the path needs to satisfy 1) all edges in the path satisfy the given weight constraints, and 2) the length of the path does not exceed the given distance threshold k. To address the problem, firstly, WKRI index supporting k -step weighted reachability query processing and index construction methods based on efficient pruning strategies are proposed. Secondly, the idea of constructing index based on part of the vertexs is proposed to reduce the size of the index. We design and implement two optimized indexes GWKRI and LWKRI based on the vertex coverage set. Finally, experiments are conducted on several real datasets. The experimental results verify the efficiency of the method proposed in this paper in answering k -step weighted reachability queries.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (27)
  1. Sengupta, N., Bagchi, A., Ramanath, M., Bedathur, S.: Arrow: Approximating reachability using random walks over web-scale graphs. In: 2019 IEEE 35th International Conference on Data Engineering (ICDE), pp. 470–481 (2019). IEEE Zhou et al. [2017] Zhou, J., Zhou, S., Yu, J.X., Wei, H., Chen, Z., Tang, X.: Dag reduction: Fast answering reachability queries. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp. 375–390 (2017) Chen and Chen [2008] Chen, Y., Chen, Y.: An efficient algorithm for answering graph reachability queries. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 893–902 (2008). IEEE Chen and Chen [2011] Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zhou, J., Zhou, S., Yu, J.X., Wei, H., Chen, Z., Tang, X.: Dag reduction: Fast answering reachability queries. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp. 375–390 (2017) Chen and Chen [2008] Chen, Y., Chen, Y.: An efficient algorithm for answering graph reachability queries. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 893–902 (2008). IEEE Chen and Chen [2011] Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, Y., Chen, Y.: An efficient algorithm for answering graph reachability queries. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 893–902 (2008). IEEE Chen and Chen [2011] Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  2. Zhou, J., Zhou, S., Yu, J.X., Wei, H., Chen, Z., Tang, X.: Dag reduction: Fast answering reachability queries. In: Proceedings of the 2017 ACM International Conference on Management of Data, pp. 375–390 (2017) Chen and Chen [2008] Chen, Y., Chen, Y.: An efficient algorithm for answering graph reachability queries. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 893–902 (2008). IEEE Chen and Chen [2011] Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, Y., Chen, Y.: An efficient algorithm for answering graph reachability queries. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 893–902 (2008). IEEE Chen and Chen [2011] Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  3. Chen, Y., Chen, Y.: An efficient algorithm for answering graph reachability queries. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 893–902 (2008). IEEE Chen and Chen [2011] Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  4. Chen, Y., Chen, Y.: Decomposing dags into spanning trees: A new way to compress transitive closures. In: 2011 IEEE 27th International Conference on Data Engineering, pp. 1007–1018 (2011). IEEE Trißl and Leser [2007] Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  5. Trißl, S., Leser, U.: Fast and practical indexing and querying of very large graphs. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 845–856 (2007) Wang et al. [2006] Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  6. Wang, H., He, H., Yang, J., Yu, P.S., Yu, J.X.: Dual labeling: Answering graph reachability queries in constant time. In: 22nd International Conference on Data Engineering (ICDE’06), pp. 75–75 (2006). IEEE Peng et al. [2020] Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  7. Peng, Y., Zhang, Y., Lin, X., Qin, L., Zhang, W.: Answering billion-scale label-constrained reachability queries within microsecond. Proceedings of the VLDB Endowment 13(6), 812–825 (2020) Chen et al. [2021] Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  8. Chen, X., Wang, K., Lin, X., Zhang, W., Qin, L., Zhang, Y.: Efficiently answering reachability and path queries on temporal bipartite graphs. Proceedings of the VLDB Endowment (2021) Choudhary and Singh [2015] Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  9. Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. International Journal of Computer Applications 112(9), 24–29 (2015) Cheng et al. [2012] Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  10. Cheng, J., Ke, Y., Chu, S., Cheng, C.: Efficient processing of distance queries in large graphs: a vertex cover approach. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, pp. 457–468 (2012) Jin et al. [2008] Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  11. Jin, R., Xiang, Y., Ruan, N., Wang, H.: Efficiently answering reachability queries on very large directed graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp. 595–608 (2008) Wen et al. [2020] Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  12. Wen, D., Huang, Y., Zhang, Y., Qin, L., Zhang, W., Lin, X.: Efficiently answering span-reachability queries in large temporal graphs. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1153–1164 (2020). IEEE Qiao et al. [2013] Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  13. Qiao, M., Cheng, H., Qin, L., Yu, J.X., Yu, P.S., Chang, L.: Computing weight constraint reachability in large networks. The VLDB journal 22(3), 275–294 (2013) Peng et al. [2023] Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  14. Peng, Y., Ma, Z., Zhang, W., Lin, X., Zhang, Y., Chen, X.: Efficiently answering quality constrained shortest distance queries in large graphs. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE), pp. 856–868 (2023). IEEE Gurukar et al. [2015] Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  15. Gurukar, S., Ranu, S., Ravindran, B.: Commit: A scalable approach to mining communication motifs from dynamic networks. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 475–489 (2015) Yano et al. [2013] Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  16. Yano, Y., Akiba, T., Iwata, Y., Yoshida, Y.: Fast and scalable reachability queries on graphs by pruned labeling with landmarks and paths. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 1601–1606 (2013) Yildirim et al. [2010] Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  17. Yildirim, H., Chaoji, V., Zaki, M.J.: Grail: Scalable reachability index for large graphs. Proceedings of the VLDB Endowment 3(1-2), 276–284 (2010) Cheng et al. [2012] Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  18. Cheng, J., Shang, Z., Cheng, H., Wang, H., Yu, J.X.: K-reach: Who is in your small world. arXiv preprint arXiv:1208.0090 (2012) Peng et al. [2022] Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  19. Peng, Y., Lin, X., Zhang, Y., Zhang, W., Qin, L.: Answering reachability and k-reach queries on large graphs with label constraints. The VLDB Journal, 1–27 (2022) Li et al. [2019] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  20. Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling distance labeling on small-world networks. In: Proceedings of the 2019 International Conference on Management of Data, pp. 1060–1077 (2019) Li et al. [2020] Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  21. Li, W., Qiao, M., Qin, L., Zhang, Y., Chang, L., Lin, X.: Scaling up distance labeling on graphs with core-periphery properties. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1367–1381 (2020) Dietrich et al. [2021] Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  22. Dietrich, J., Chang, L., Qian, L., Henry, L.M., McCartin, C., Scholz, B.: Efficient sink-reachability analysis via graph reduction. IEEE Transactions on Knowledge and Data Engineering 34(11), 5321–5335 (2021) Chen et al. [2022] Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  23. Chen, X., Peng, Y., Wang, S., Yu, J.X.: Dlcr: efficient indexing for label-constrained reachability queries on large dynamic graphs. Proceedings of the VLDB Endowment 15(8), 1645–1657 (2022) Zeng et al. [2022] Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  24. Zeng, Y., Yang, W., Zhou, X., Xiao, G., Gao, Y., Li, K.: Distributed set label-constrained reachability queries over billion-scale graphs. In: 2022 IEEE 38th International Conference on Data Engineering (ICDE), pp. 1969–1981 (2022). IEEE Bundy [1986] Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  25. Bundy, A.: Catalogue of artificial intelligence tools. In: Catalogue of Artificial Intelligence Tools, pp. 7–161 (1986). Springer Veloso et al. [2014] Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  26. Veloso, R.R., Cerf, L., Meira Jr, W., Zaki, M.J.: Reachability queries in very large graphs: A fast refined online search approach. In: EDBT, pp. 511–522 (2014). Citeseer Brešar et al. [2011] Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011) Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)
  27. Brešar, B., Kardoš, F., Katrenič, J., Semanišin, G.: Minimum k-path vertex cover. Discrete Applied Mathematics 159(12), 1189–1195 (2011)

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now