Rank-Ordering Documents According to Their Relevance in Information Retrieval Using Refinements of Ordered-Weighted Aggregations

  • Mohand Boughanem
  • Yannick Loiseau
  • Henri Prade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3877)


Classical information retrieval methods often lose valuable information when aggregating weights, which may diminish the discriminating power between documents. To cope with this problem, the paper presents an approach for ranking documents in IR, based on a vector-based ordering technique already considered in fuzzy logic for multiple criteria analysis purpose. Moreover, the proposed approach uses a possibilistic framework for evaluating queries to a document collection, which distinguishes between descriptors that are certainly relevant and those which are possibly relevant only. The proposal is evaluated on a benchmark collection that allows us to compare the effectiveness of this approach with a classical one. The proposed method provides an improvement of the precision w.r.t Mercure IR system.


Information Retrieval Relevant Document Query Term Information Retrieval System Term Weight 
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

  • Mohand Boughanem
    • 1
  • Yannick Loiseau
    • 1
  • Henri Prade
    • 1
  1. 1.Institut de recherche en informatique de ToulouseToulouse

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