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A Survey on Bundle Recommendation: Methods, Applications, and Challenges

Published 1 Nov 2024 in cs.IR | (2411.00341v1)

Abstract: In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by recommending a set of items as a bundle rather than individual items. This survey provides a comprehensive review on bundle recommendation, beginning by a taxonomy for exploring product bundling. We classify it into two categories based on bundling strategy from various application domains, i.e., discriminative and generative bundle recommendation. Then we formulate the corresponding tasks of the two categories and systematically review their methods: 1) representation learning from bundle and item levels and interaction modeling for discriminative bundle recommendation; 2) representation learning from item level and bundle generation for generative bundle recommendation. Subsequently, we survey the resources of bundle recommendation including datasets and evaluation metrics, and conduct reproducibility experiments on mainstream models. Lastly, we discuss the main challenges and highlight the promising future directions in the field of bundle recommendation, aiming to serve as a useful resource for researchers and practitioners. Our code and datasets are publicly available at https://github.com/WUT-IDEA/bundle-recommendation-survey.

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References (186)
  1. DIETOS: A Recommender System for Health Profiling and Diet Management in Chronic Diseases.. In HealthRecSys@ RecSys. 32–35.
  2. Improving Bundles Recommendation Coverage in Sparse Product Graphs. In Companion Proceedings of the Web Conference 2022 (WWW ’22). Association for Computing Machinery, 1037–1045.
  3. BRUCE: Bundle Recommendation Using Contextualized item Embeddings. In Proceedings of the 16th ACM Conference on Recommender Systems (RecSys ’22). Association for Computing Machinery, 237–245.
  4. Personalized Bundle List Recommendation. In The World Wide Web Conference (WWW ’19). Association for Computing Machinery, 60–71.
  5. Boxrec: Recommending a Box of Preferred Outfits in Online Shopping. ACM Transactions on Intelligent Systems and Technology (TIST) 11, 6 (2020), 1–28.
  6. Recommender Systems for Product Bundling. Knowledge-Based Systems 111 (2016), 193–206.
  7. Idir Benouaret and Dominique Lenne. 2016. A Package Recommendation Framework for Trip Planning Activities. In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys ’16). Association for Computing Machinery, 203–206.
  8. Idir Benouaret and Dominique Lenne. 2017. Recommending Diverse and Personalized Travel Packages. In Database and Expert Systems Applications. Springer International Publishing, Cham, 325–339.
  9. Empirical Analysis of Predictive Algorithms for Collaborative Filtering. In UAI ’98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, Wisconsin, USA, July 24-26, 1998. Morgan Kaufmann, 43–52.
  10. A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Apps. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD ’21). Association for Computing Machinery, 2601–2609.
  11. Embedding Factorization Models for Jointly Recommending Items and User Generated Lists. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’17). Association for Computing Machinery, 585–594.
  12. Service Package Recommendation for Mashup Development Based on a Multi-level Relational Network. In Service-Oriented Computing. Springer International Publishing, Cham, 666–674.
  13. Hyperbolic Graph Convolutional Neural Networks. In Advances in Neural Information Processing Systems, Vol. 32. Curran Associates, Inc.
  14. Bundle Recommendation with Graph Convolutional Networks. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’20). Association for Computing Machinery, 1673–1676.
  15. Bundle Recommendation and Generation with Graph Neural Networks. IEEE Transactions on Knowledge and Data Engineering 35, 3 (2021), 2326–2340.
  16. Learning Points and Routes to Recommend Trajectories. In Proceedings of the 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, USA, October 24-28, 2016. ACM, 2227–2232.
  17. Bias and Debias in Recommender System: A Survey and Future Directions. ACM Transactions on Information Systems 41, 3 (2023), 1–39.
  18. Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19 (IJCAI ’19). International Joint Conferences on Artificial Intelligence Organization, 2095–2101.
  19. POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery Data Mining (KDD ’19). Association for Computing Machinery, 2662–2670.
  20. Deep Reinforcement Learning in Recommender Systems: A Survey and New Perspectives. Knowledge-Based Systems 264 (2023), 110335.
  21. A Package Generation and Recommendation Framework Based on Travelogues. In 2015 IEEE 39th Annual Computer Software and Applications Conference, Vol. 2. 692–701.
  22. Recommender Systems for Online Video Game Platforms: the Case of STEAM. In Companion Proceedings of The 2019 World Wide Web Conference (WWW ’19). Association for Computing Machinery, 763–771.
  23. Balanced Quality Score: Measuring Popularity Debiasing in Recommendation. ACM Trans. Intell. Syst. Technol. 15, 4 (2024), 1–27.
  24. Deep Neural Networks for Youtube Recommendations. In Proceedings of the 10th ACM conference on recommender systems. 191–198.
  25. Uncovering Chatgpt’s Capabilities in Recommender Systems. In Proceedings of the 17th ACM Conference on Recommender Systems. 1126–1132.
  26. Google News Personalization: Scalable Online Collaborative Filtering. In Proceedings of the 16th international conference on World Wide Web. 271–280.
  27. Fairness in Recommender Systems: Research Landscape and Future Directions. User Modeling and User-Adapted Interaction 34, 1 (2024), 59–108.
  28. Build Your Own Bundle - A Neural Combinatorial Optimization Method. In Proceedings of the 29th ACM International Conference on Multimedia (MM ’21). Association for Computing Machinery, 2625–2633.
  29. Personalized Bundle Recommendation in Online Games. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management (CIKM ’20). Association for Computing Machinery, 2381–2388.
  30. Multi-Aspect Interest Neighbor-Augmented Network for Next-Basket Recommendation. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 1–5.
  31. Multi-view Multi-aspect Neural Networks for Next-basket Recommendation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’23). Association for Computing Machinery, 1283–1292.
  32. Mukund Deshpande and George Karypis. 2004. Item-based Top-n Recommendation Algorithms. ACM Transactions on Information Systems (TOIS) 22, 1 (2004), 143–177.
  33. Personalized Fashion Outfit Generation with User Coordination Preference Learning. Information Processing & Management 60, 5 (2023), 103434.
  34. Enhancing Item-level Bundle Representation for Bundle Recommendation. ACM Transactions on Recommender Systems (2023).
  35. David Elsweiler and Morgan Harvey. 2015. Towards Automatic Meal Plan Recommendations for Balanced Nutrition. In Proceedings of the 9th ACM Conference on Recommender Systems. 313–316.
  36. Trip Recommendation with Multiple User Constraints by Integrating Point-of-interests and Travel Packages. In 2014 IEEE 15th International Conference on Mobile Data Management (MDM ’14, Vol. 1). IEEE, 33–42.
  37. Customized Bundle Recommendation by Association Rules of Product Categories for Online Supermarkets. In 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). IEEE, 472–475.
  38. Cross-Platform Item Recommendation for Online Social E-Commerce. IEEE Transactions on Knowledge and Data Engineering 35, 2 (2023), 1351–1364.
  39. Self-supervised Representation Learning for Trip Recommendation. Knowl. Based Syst. 247 (2022), 108791.
  40. Adversarial Human Trajectory Learning for Trip Recommendation. IEEE Trans. Neural Networks Learn. Syst. 34, 4 (2023), 1764–1776.
  41. Design of A Shopbot and Recommender System for Bundle Purchases. Decision Support Systems 42, 3 (2006), 1974–1986.
  42. Carlos A. Gomez-Uribe and Neil Hunt. 2016. The Netflix Recommender System: Algorithms, Business Value, and Innovation. ACM Trans. Manage. Inf. Syst. 6, 4 (2016).
  43. Enhancing Personalized Trip Recommendation with Attractive Routes. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020. AAAI Press, 662–669.
  44. Csbr: A Compositional Semantics-based Service Bundle Recommendation Approach for Mashup Development. IEEE Transactions on Services Computing 15, 6 (2021), 3170–3183.
  45. Service Package Recommendation for Mashup Creation via Mashup Textual Description Mining. In 2016 IEEE international conference on web services (ICWS) (ICWS ’16). IEEE, 452–459.
  46. Liu Guo-rong and Zhang Xi-zheng. 2006. Collaborative Filtering Based Recommendation System for Product Bundling. In 2006 International Conference on Management Science and Engineering. IEEE, 251–254.
  47. Social Media Recommendation Based on People and Tags. In Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval. 194–201.
  48. Learning Fashion Compatibility with Bidirectional LSTMs. In Proceedings of the 25th ACM International Conference on Multimedia (MM ’17). Association for Computing Machinery, New York, NY, USA, 1078–1086.
  49. Leveraging Large Language Models for Sequential Recommendation. In Proceedings of the 17th ACM Conference on Recommender Systems. 1096–1102.
  50. SocoTraveler: Travel-package Recommendations Leveraging Social Influence of Different Relationship Types. Information & Management 53, 8 (2016), 934–950.
  51. A Joint Context-Aware Embedding for Trip Recommendations. In 2019 IEEE 35th International Conference on Data Engineering (ICDE). 292–303.
  52. Lightgcn: Simplifying and Powering Graph Convolution Network for Recommendation. In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval. 639–648.
  53. Neural Collaborative Filtering. In Proceedings of the 26th international conference on world wide web. 173–182.
  54. A Hierarchical Self-attentive Model for Recommending User-generated Item Lists. In Proceedings of the 28th ACM international conference on information and knowledge management. 1481–1490.
  55. Consistency-Aware Recommendation for User-Generated Item List Continuation. In Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM ’20). Association for Computing Machinery, 250–258.
  56. Large Language Models as Zero-shot Conversational Recommenders. In Proceedings of the 32nd ACM international conference on information and knowledge management. 720–730.
  57. Bundle MCR: Towards Conversational Bundle Recommendation. In Proceedings of the 16th ACM Conference on Recommender Systems (RecSys ’22). 288–298.
  58. Integrating Route Attractiveness Attributes into Tourist Trip Recommendations. In Companion Proceedings of The 2019 World Wide Web Conference. 96–101.
  59. Collaborative Fashion Recommendation: A Functional Tensor Factorization Approach. In Proceedings of the 23rd ACM international conference on Multimedia. 129–138.
  60. A Versatile Graph-based Approach to Package Recommendation. In 2013 IEEE 25th International Conference on Tools with Artificial Intelligence (ICTAI ’13). IEEE, 857–864.
  61. Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’23). Springer, 348–360.
  62. Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating. In Proceedings of the ACM on Web Conference 2024 (WWW ’24). Association for Computing Machinery, 3277–3286.
  63. MIMIC-III, A Freely Accessible Critical Care Database. Scientific data 3, 1 (2016), 1–9.
  64. A Probabilistic Model for Diversifying Recommendation Lists. In Web Technologies and Applications: 15th Asia-Pacific Web Conference, APWeb 2013, Sydney, Australia, April 4-6, 2013. Proceedings 15. Springer, 348–359.
  65. DE-RRD: A Knowledge Distillation Framework for Recommender System. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management. 605–614.
  66. Personalised News and Blog Recommendations Based on User Location, Facebook and Twitter User Profiling. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval. 1129–1132.
  67. Hyperbolic Mutual Learning for Bundle Recommendation. In International Conference on Database Systems for Advanced Applications. Springer Nature Switzerland, 417–433.
  68. Tree-Like Interaction Learning for Bundle Recommendation. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (ICASSP ’23). 1–5.
  69. Less is More: A Streamlined Graph-Based Fashion Outfit Recommendation without Multimodal Dependency. In Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing (SAC ’24). Association for Computing Machinery, 492–495.
  70. Matrix Factorization Techniques for Recommender Systems. Computer 42, 8 (2009), 30–37.
  71. Bidirectional Distillation for Top-K Recommender System. In Proceedings of the Web Conference 2021. 3861–3871.
  72. Collaborative Distillation for Top-N Recommendation. In 2019 IEEE International Conference on Data Mining (ICDM). IEEE, 369–378.
  73. List Recommendation via Co-attentive User Preference Fine-tuning. In International Conference on Neural Information Processing. Springer, 554–562.
  74. Multiple: Multi-level User Preference Learning for List Recommendation. In International Conference on Web Information Systems Engineering. Springer, 221–236.
  75. Package Recommendation with Intra-and Inter-package Attention Networks. In Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval. 595–604.
  76. Blip: Bootstrapping Language-image Pre-training for Unified Vision-language Understanding and Generation. In International conference on machine learning. PMLR, 12888–12900.
  77. A Survey of Researches on Personalized Bundle Recommendation Techniques. In Machine Learning for Cyber Security. ML4CS 2020 (Lecture Notes in Computer Science, Vol. 12487). Springer, Cham, 393–405.
  78. MealRec+: A Meal Recommendation Dataset with Meal-Course Affiliation for Personalization and Healthiness. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24). Association for Computing Machinery, 564–574.
  79. Category-Wise Meal Recommendation. In International Conference on Neural Information Processing. Springer, 282–294.
  80. Boosting Healthiness Exposure in Category-constrained Meal Recommendation Using Nutritional Standards. ACM Transactions on Intelligent Systems and Technology (2024).
  81. User-Meal Interaction Learning for Meal Recommendation: A Reproducibility Study. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region. 104–113.
  82. MealRec: A Meal Recommendation Dataset. arXiv preprint arXiv:2205.12133 (2022).
  83. Next Basket Recommendation with Intent-aware Hypergraph Adversarial Network. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023. ACM, 1303–1312.
  84. Hierarchical Fashion Graph Network for Personalized Outfit Recommendation. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval. 159–168.
  85. Auto Graph Filtering for Bundle Recommendation. In 2023 IEEE International Conference on Data Mining (ICDM). IEEE, 299–308.
  86. Mining Fashion Outfit Composition Using an End-to-End Deep Learning Approach on Set Data. IEEE Transactions on Multimedia 19, 8 (2017), 1946–1955.
  87. Personalized Tour Recommendation Based on User Interests and Points of Interest Visit Durations. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015. AAAI Press, 1778–1784.
  88. Personalized Trip Recommendation for Tourists Based on User Interests, Points of Interest Visit Durations and Visit Recency. Knowledge and Information Systems 54 (2018), 375–406.
  89. Amazon. com Recommendations: Item-to-item Collaborative Filtering. IEEE Internet computing 7, 1 (2003), 76–80.
  90. The Geometry of Graphs and Some of Its Algorithmic Applications. Combinatorica 15 (1995), 215–245.
  91. Modeling Buying Motives for Personalized Product Bundle Recommendation. ACM Transactions on Knowledge Discovery from Data (TKDD) 11, 3 (2017), 1–26.
  92. Personalized News Recommendation Based on Click Behavior. In Proceedings of the 15th international conference on Intelligent user interfaces. 31–40.
  93. Hypergrah-Enhanced Dual Convolutional Network for Bundle Recommendation. arXiv preprint arXiv:2312.11018 (2023).
  94. DySR: A Dynamic Graph Neural Network Based Service Bundle Recommendation Model for Mashup Creation. IEEE Transactions on Services Computing 16, 4 (2023), 2592–2605.
  95. DySR: A Dynamic Representation Learning and Aligning based Model for Service Bundle Recommendation. arXiv preprint arXiv:2108.03360 (2021).
  96. Personalized Travel Package Recommendation. In 11th IEEE International Conference on Data Mining, ICDM 2011, Vancouver, BC, Canada, December 11-14, 2011. IEEE Computer Society, 407–416.
  97. Hi, Magic Closet, Tell Me What to Wear!. In Proceedings of the 20th ACM international conference on Multimedia. 619–628.
  98. Harnessing Large Language Models for Multimodal Product Bundling. CoRR abs/2407.11712 (2024). arXiv:2407.11712
  99. Yancen Liu and Jian Cao. 2020. API-Prefer: An API Package Recommender System Based on Composition Feature Learning. In Service-Oriented Computing - 18th International Conference, ICSOC 2020, Dubai, United Arab Emirates, December 14-17, 2020, Proceedings (Lecture Notes in Computer Science, Vol. 12571). Springer, 500–507.
  100. Recommending User Generated Item Lists. In Proceedings of the 8th ACM Conference on Recommender systems. 185–192.
  101. Basconv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network. In Proceedings of the 2020 SIAM International Conference on Data Mining. SIAM, 64–72.
  102. Gaussian Graph with Prototypical Contrastive Learning in E-Commerce Bundle Recommendation. arXiv preprint arXiv:2307.13468 (2023).
  103. Content-based Recommender Systems: State of the Art and Trends. Recommender systems handbook (2011), 73–105.
  104. Learning Distinct Relationship in Package Recommendation with Graph Attention Networks. IEEE Transactions on Computational Social Systems (2022).
  105. Content-based Collaborative Filtering for News Topic Recommendation. In Proceedings of the AAAI conference on artificial intelligence, Vol. 29.
  106. Learning Binary Code for Personalized Fashion Recommendation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  107. Pengfei Ma and Yong Zhang. 2013. MAKM: A MAFIA-Based k-Means Algorithm for Short Text in Social Networks. In Database Systems for Advanced Applications, 18th International Conference, DASFAA 2013, Wuhan, China, April 22-25, 2013. Proceedings, Part II (Lecture Notes in Computer Science). Springer, 210–218.
  108. MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation. ACM Trans. Inf. Syst. 42, 4 (2024), 100:1–100:23.
  109. CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’22). Association for Computing Machinery, 1233–1241.
  110. CIRP: Cross-Item Relational Pre-training for Multimodal Product Bundling. arXiv preprint arXiv:2404.01735 (2024).
  111. Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining. 510–519.
  112. Inferring Networks of Substitutable and Complementary Products. In Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining. 785–794.
  113. Image-based Recommendations on Styles and Substitutes. In Proceedings of the 38th international ACM SIGIR conference on research and development in information retrieval. 43–52.
  114. Brian McFee and Gert RG Lanckriet. 2012. Hypergraph Models of Playlist Dialects.. In ISMIR, Vol. 12. 343–348.
  115. Food Recommendation: Framework, Existing Solutions, and Challenges. IEEE Trans. Multim. 22, 10 (2020), 2659–2671.
  116. Bundle Recommendation with Item-Level Causation-Enhanced Multi-view Learning. In Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track - European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9-13, 2024, Proceedings, Part VIII (Lecture Notes in Computer Science, Vol. 14948). Springer, 324–341.
  117. Embedding-based News Recommendation for Millions of Users. In Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining. 1933–1942.
  118. Generating and Personalizing Bundle Recommendations on Steam. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’17). Association for Computing Machinery, 1073–1076.
  119. Michael J Pazzani and Daniel Billsus. 2007. Content-based Recommendation Systems. In The adaptive web: methods and strategies of web personalization. Springer, 325–341.
  120. Using Twitter to Recommend Real-time Topical News. In Proceedings of the third ACM conference on Recommender systems. 385–388.
  121. API-PROGRAM: An API Package Recommendation Model Based on the Graph Representation Learning Method. In Service-Oriented Computing - 19th International Conference, ICSOC 2021, Virtual Event, November 22-25, 2021, Proceedings (Lecture Notes in Computer Science, Vol. 13121). Springer, 859–866.
  122. Distillation-Enhanced Graph Masked Autoencoders for Bundle Recommendation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’23). 1660–1669.
  123. BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009. AUAI Press, 452–461.
  124. Factorizing Personalized Markov Chains for Next-basket Recommendation. In Proceedings of the 19th international conference on World wide web. 811–820.
  125. Representation Tradeoffs for Hyperbolic Embeddings. In International conference on machine learning. PMLR, 4460–4469.
  126. Multi-view Denoising Contrastive Learning for Bundle Recommendation. Applied Intelligence (2024), 1–15.
  127. Item-based Collaborative Filtering Recommendation Algorithms. In Proceedings of the 10th international conference on World Wide Web. 285–295.
  128. Collaborative Filtering Recommender Systems. In The adaptive web: methods and strategies of web personalization. Springer, 291–324.
  129. Hierarchical Alignment With Polar Contrastive Learning for Next-Basket Recommendation. IEEE Trans. Knowl. Data Eng. 36, 1 (2024), 199–210.
  130. IMBR: Interactive Multi-relation Bundle Recommendation with Graph Neural Network. In International Conference on Wireless Algorithms, Systems, and Applications (WASA ’22). Springer, 460–472.
  131. Self-supervised Continual Graph Learning in Adaptive Riemannian Spaces. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 37. 4633–4642.
  132. Contrastive Sequential Interaction Network Learning on Co-evolving Riemannian Spaces. International Journal of Machine Learning and Cybernetics 15, 4 (2024), 1397–1413.
  133. Generative Next-Basket Recommendation. In Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023, Singapore, Singapore, September 18-22, 2023. ACM, 737–743.
  134. Revisiting Bundle Recommendation for Intent-aware Product Bundling. Trans. Recomm. Syst. 2, 3 (2024), 24:1–24:34.
  135. Dynamic In-Context Learning from Nearest Neighbors for Bundle Generation. CoRR abs/2312.16262 (2023). arXiv:2312.16262
  136. Adaptive In-Context Learning with Large Language Models for Bundle Generation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. 966–976.
  137. Revisiting Bundle Recommendation: Datasets, Tasks, Challenges and Opportunities for Intent-aware Product Bundling. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22). Association for Computing Machinery, 2900–2911.
  138. Intention-oriented Hierarchical Bundle Recommendation with Preference Transfer. In 2021 IEEE International Conference on Web Services (ICWS). IEEE, 107–116.
  139. Knowledge-based Recommendation: A Review of Ontology-based Recommender Systems for E-learning. Artificial Intelligence Review 50 (2018), 21–48.
  140. Deep content-based music recommendation. In Advances in Neural Information Processing Systems, Vol. 26. Curran Associates, Inc.
  141. GRAM-SMOT: Top-N Personalized Bundle Recommendation via Graph Attention Mechanism and Submodular Optimization. In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 297–313.
  142. Representing and Recommending Shopping Baskets with Complementarity, Compatibility and Loyalty. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM ’18). 1133–1142.
  143. Cross-level Relational Graph Contrastive Learning for Bundle Recommendation. In 2023 IEEE International Conference on Web Services (ICWS) (ICWS ’23). IEEE, 112–117.
  144. Peipei Wang and Lin Li. 2021. BERT-based Aggregative Group Representation for Group Recommendation. In 8th International Conference on Behavioral and Social Computing, BESC 2021, Doha, Qatar, October 29-31, 2021. IEEE, 1–7.
  145. Query2Trip: Dual-Debiased Learning for Neural Trip Recommendation. In Database Systems for Advanced Applications - 28th International Conference, DASFAA 2023, Tianjin, China, April 17-20, 2023, Proceedings, Part II (Lecture Notes in Computer Science, Vol. 13944). Springer, 80–96.
  146. Socially-driven Multi-interaction Attentive Group Representation Learning for Group Recommendation. Pattern Recognit. Lett. 145 (2021), 74–80.
  147. Social Dual-effect Driven Group Modeling for Neural Group Recommendation. Neurocomputing 481 (2022), 258–269.
  148. Neural Graph Collaborative Filtering. In Proceedings of the 42nd international ACM SIGIR conference on Research and development in Information Retrieval. 165–174.
  149. Relational Graph Neural Network with Neighbor Interactions for Bundle Recommendation Service. In 2021 IEEE International Conference on Web Services (ICWS) (ICWS ’21). IEEE, 167–172.
  150. A Survey on the Fairness of Recommender Systems. ACM Transactions on Information Systems 41, 3 (2023), 1–43.
  151. Towards Personalized Bundle Creative Generation with Contrastive Non-Autoregressive Decoding. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22). Association for Computing Machinery, 2634–2638.
  152. Strategy-aware Bundle Recommender system. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’23). Association for Computing Machinery, 1198–1207.
  153. Dual-Supervised Contrastive Learning for Bundle Recommendation. IEEE Trans. Comput. Soc. Syst. 11, 3 (2024), 3955–3965.
  154. A Survey on Accuracy-Oriented Neural Recommendation: From Collaborative Filtering to Information-Rich Recommendation. IEEE Transactions on Knowledge and Data Engineering 35, 5 (2023), 4425–4445.
  155. Large-scale Contrastive Language-audio Pretraining with Feature Fusion and Keyword-to-caption Augmentation. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 1–5.
  156. Breaking out of the Box of Recommendations: From Items to Packages. In Proceedings of the fourth ACM conference on Recommender systems (RecSys ’10). Association for Computing Machinery, 151–158.
  157. Generating Top-k Packages via Preference Elicitation. Proc. VLDB Endow. 7, 14 (oct 2014), 1941–1952.
  158. C3BR: Category-Aware Cross-View Contrastive Learning Framework for Bundle Recommendation. In Database Systems for Advanced Applications. DASFAA 2023 International Workshops. Springer Nature Switzerland, 194–203.
  159. Diffusion Models for Generative Outfit Recommendation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’24). Association for Computing Machinery, 1350–1359.
  160. Gated and Attentive Neural Collaborative Filtering for User Generated List Recommendation. Knowledge-based systems 187 (2020), 104839.
  161. Music Playlist Recommendation with Long Short-term Memory. In Database Systems for Advanced Applications: 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22–25, 2019, Proceedings, Part II 24. Springer, 416–432.
  162. A Heterogeneous Graph Neural Network Model for List Recommendation. Knowledge-Based Systems 277 (2023), 110822.
  163. Multi-view Attentive Variational Learning for Group Recommendation. In 40th IEEE International Conference on Data Engineering, ICDE 2024, Utrecht, The Netherlands, May 13-16, 2024. IEEE, 5022–5034.
  164. Non-autoregressive Personalized Bundle Generation. Inf. Process. Manag. 61, 5 (2024), 103814.
  165. Productrec: Product Bundle Recommendation Based on User’s Sequential Patterns in Social Networking Service Environment. In 2017 IEEE International Conference on Web Services (ICWS) (ICWS ’17). IEEE, 301–308.
  166. Basket Representation Learning by Hypergraph Convolution on Repeated Items for Next-basket Recommendation. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023, 19th-25th August 2023, Macao, SAR, China. ijcai.org, 2415–2422.
  167. Unifying Multi-associations Through Hypergraph for Bundle Recommendation. Knowledge-Based Systems 255 (2022), 109755.
  168. Personalized Travel Package with Multi-point-of-interest Recommendation Based on Crowdsourced User Footprints. IEEE Transactions on Human-Machine Systems 46, 1 (2015), 151–158.
  169. Encoder-Decoder Based Route Generation Model for Flexible Travel Recommendation. IEEE Trans. Serv. Comput. 17, 3 (2024), 905–920.
  170. Where Are We in Embedding Spaces?. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD ’21). Association for Computing Machinery, 2223–2231.
  171. Dual-target Cross-domain Bundle Recommendation. In 2021 IEEE International Conference on Services Computing (SCC). IEEE, 183–192.
  172. Yongfeng Zhang and Xu Chen. 2020. Explainable Recommendation: A Survey and New Perspectives. Foundations and Trends® in Information Retrieval 14, 1 (2020), 1–101.
  173. Suger: A Subgraph-based Graph Convolutional Network Method for Bundle Recommendation. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM ’22). 4712–4716.
  174. Photo2Trip: Exploiting Visual Contents in Geo-Tagged Photos for Personalized Tour Recommendation. IEEE Transactions on Knowledge and Data Engineering 33, 4 (2021), 1708–1721.
  175. Multi-view Intent Disentangle Graph Networks for Bundle Recommendation. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI ’22, Vol. 36). 4379–4387.
  176. DHMAE: A Disentangled Hypergraph Masked Autoencoder for Group Recommendation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024 (SIGIR ’24). ACM, 914–923.
  177. Interaction-aware Drug Package Recommendation via Policy Gradient. ACM Transactions on Information Systems 41, 1 (2023), 1–32.
  178. Contrastive Trajectory Learning for Tour Recommendation. ACM Trans. Intell. Syst. Technol. 13, 1 (2022), 4:1–4:25.
  179. Context-aware Variational Trajectory Encoding and Human Mobility Inference. In The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019. ACM, 3469–3475.
  180. Medicine Package Recommendation via Dual-level Interaction Aware Heterogeneous Graph. IEEE Journal of Biomedical and Health Informatics (2024).
  181. A Multi-task Graph Neural Network with Variational Graph Auto-encoders for Session-based Travel Packages Recommendation. ACM Transactions on the Web 17, 3 (2023), 1–30.
  182. Neural Attentive Travel Package Recommendation via Exploiting Long-term and Short-term Behaviors. Knowledge-Based Systems 211 (2021), 106511.
  183. Text2Bundle: Towards Personalized Query-based Bundle Generation. CoRR abs/2310.18004 (2023). arXiv:2310.18004
  184. Data-augmented Counterfactual Learning for Bundle Recommendation. In International Conference on Database Systems for Advanced Applications. Springer, 314–330.
  185. Bundle Recommendation in Ecommerce. In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR ’14). Association for Computing Machinery, 657–666.
  186. Towards Hierarchical Intent Disentanglement for Bundle Recommendation. IEEE Trans. Knowl. Data Eng. 36, 7 (2024), 3556–3567.

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