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Concept Embedding for Information Retrieval
February 01, 2020 Β· Declared Dead Β· π European Conference on Information Retrieval
"No code URL or promise found in abstract"
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Authors
Karam Abdulahhad
arXiv ID
2002.01071
Category
cs.IR: Information Retrieval
Cross-listed
cs.AI,
cs.CL,
cs.LG
Citations
2
Venue
European Conference on Information Retrieval
Last Checked
4 months ago
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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