ENSM-SE at CLEF 2005: using a fuzzy proximity matching function

  • Authors:
  • Annabelle Mercier;Amélie Imafouo;Michel Beigbeder

  • Affiliations:
  • École Nationale Supérieure des Mines de Saint-Étienne, Saint-Etienne, France;École Nationale Supérieure des Mines de Saint-Étienne, Saint-Etienne, France;École Nationale Supérieure des Mines de Saint-Étienne, Saint-Etienne, France

  • Venue:
  • CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
  • Year:
  • 2005

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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.