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ENSM-SE at INEX 2009 : Scoring with Proximity and Semantic Tag Information

  • Michel Beigbeder
  • Amélie Imafouo
  • Annabelle Mercier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6203)

Abstract

We present in this paper some experiments on the Wikipedia collection used in the INEX 2009 evaluation campaign with an information retrieval method based on proximity. The idea of the method is to assign to each position in the document a fuzzy proximity value depending on its closeness to the surrounding keywords. These proximity values can then be summed on any range of text – including any passage or any element – and after normalization this sum is used as the relevance score for the extent. To take into account the semantic tags, we define a contextual operator which allow to consider at query time only the occurrences of terms that appear in a given semantic context.

Keywords

Query Time Query Term Relevance Score Semantic Context Conjunctive Query 
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 2010

Authors and Affiliations

  • Michel Beigbeder
    • 1
  • Amélie Imafouo
    • 1
  • Annabelle Mercier
    • 2
  1. 1.École Nationale Supérieure des Mines de Saint-ÉtienneSaint Etienne Cedex 2France
  2. 2.LCIS Lab - Grenoble UniversityValence Cedex 9France

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