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Concept Embedding for Information Retrieval (2002.01071v1)

Published 1 Feb 2020 in cs.IR, cs.AI, cs.CL, and cs.LG

Abstract: Concepts are used to solve the term-mismatch problem. However, we need an effective similarity measure between concepts. Word embedding presents a promising solution. We present in this study three approaches to build concepts vectors based on words vectors. We use a vector-based measure to estimate inter-concepts similarity. Our experiments show promising results. Furthermore, words and concepts become comparable. This could be used to improve conceptual indexing process.

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