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.
@article{arxiv.2002.01071,
title = {Concept Embedding for Information Retrieval},
author = {Karam Abdulahhad},
journal= {arXiv preprint arXiv:2002.01071},
year = {2020}
}