Abstract
Starting from the idea that the closer the query terms in a document are to each other the more relevant the document, we propose an information retrieval method that uses the degree of fuzzy proximity of key terms in a document to compute the relevance of the document to the query. Our model handles Boolean queries but, contrary to the traditional extensions of the basic Boolean information retrieval model, does not use a proximity operator explicitly. A single parameter makes it possible to control the proximity degree required. We explain how we construct the queries and report the results of our experiments in the ad-hoc monolingual French task of the CLEF 2005 evaluation campaign.
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Mercier, A., Imafouo, A., Beigbeder, M. (2006). ENSM-SE at CLEF 2005: Using a Fuzzy Proximity Matching Function. In: Peters, C., et al. Accessing Multilingual Information Repositories. CLEF 2005. Lecture Notes in Computer Science, vol 4022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11878773_21
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DOI: https://doi.org/10.1007/11878773_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45697-1
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