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2019 | OriginalPaper | Buchkapitel

Pseudo-Relevance Feedback Based on Locally-Built Co-occurrence Graphs

verfasst von : Billel Aklouche, Ibrahim Bounhas, Yahya Slimani

Erschienen in: Advances in Databases and Information Systems

Verlag: Springer International Publishing

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Abstract

In Information Retrieval (IR), user queries are often too short, making the selection of relevant documents hard. Pseudo-relevance feedback (PRF) is an effective method to automatically expand the query with new terms using a set of pseudo-relevant documents. However, a main issue in PRF is the selection of good expansion terms that allow improving retrieval effectiveness. In this paper, we present a new PRF method based on locally-built term co-occurrence graphs. We use a context window-based approach to construct our term co-occurrence graphs over top pseudo-relevant documents. For expansion terms selection, we propose an adapted version of the BM25 model, which allows to measure term-term similarity in co-occurrence graphs. This measure has the advantage of selecting discriminant expansion terms that are semantically related to the query as a whole. We evaluate our PRF method using four TREC collections, including the standard TREC Robust04 collection and the newest TREC Washington Post collection. Experimental results show that our proposal outperforms competitive state-of-the-art baselines and achieves significant improvements.

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Titel: Pseudo-Relevance Feedback Based on Locally-Built Co-occurrence Graphs
verfasst von: Billel Aklouche
Ibrahim Bounhas
Yahya Slimani
Verlag: Springer International Publishing
Buch: Advances in Databases and Information Systems
Print ISBN: 978-3-030-28729-0

Electronic ISBN: 978-3-030-28730-6

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-28730-6_7

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