ENSM-SE at CLEF 2005: Using a Fuzzy Proximity Matching Function

  • Annabelle Mercier
  • Amélie Imafouo
  • Michel Beigbeder
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


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.


Information Retrieval Boolean Model Proximity Operator Query Tree Information Retrieval Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Annabelle Mercier
    • 1
  • Amélie Imafouo
    • 1
  • Michel Beigbeder
    • 1
  1. 1.École Nationale Supérieure des Mines de Saint-ÉtienneSaint-EtienneFrance

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