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Revisiting the Term Frequency in Concept-Based IR Models

  • Karam Abdulahhad
  • Jean-Pierre Chevallet
  • Catherine Berrut
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8055)

Abstract

Indexing documents and queries using concepts, instead of word-based indexing, is an alternative approach, and it supposes to give a more meaningful indexing. However, this way of indexing needs to revisit some hypotheses of classical Information Retrieval. Therefore, we propose a new concept weighting approach, namely Relative Weight, which weights concepts with respect to their corresponding text in the documents or queries. In other words, it assigns to each concept a relative weight with respect to the other concepts in the same context. We explore interesting experimental results of our new weighting approach, compared to the classical approaches, through studying the retrieval performance of some classical IR models.

Keywords

Term Frequency Retrieval Performance Mean Average Precision Mapping Tool Weighting Approach 
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 2013

Authors and Affiliations

  • Karam Abdulahhad
    • 1
  • Jean-Pierre Chevallet
    • 2
  • Catherine Berrut
    • 3
  1. 1.Université de GrenobleFrance
  2. 2.UPMF-Grenoble 2France
  3. 3.LIG Laboratory, MRIM GroupUJF-Grenoble 1GrenobleFrance

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