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Context-Based Query Expansion Method for Short Queries Using Latent Semantic Analyses

  • Btihal El GhaliEmail author
  • Abderrahim El Qadi
  • Mohamed Ouadou
  • Driss Aboutajdine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9466)

Abstract

Short queries are the key difficulty in information retrieval (IR). A plenty of query expansion techniques has been proposed to solve this problem. In this paper, we propose three different models for query suggestion using the cosine similarity (CS), the Language Models (LM) or their fusion. The expansion terms are selected using the Latent Semantic Analyses method based on the result of the three query suggestion methods. The approaches proposed improve the precision of the user query by adding additional context to it. Experimental results show that expanding short queries by our approaches improves the effectiveness of the IR system by 48,1 % using the CS based model, 19,2 % using the LM model, and 13,5 % using the fusion model.

Keywords

Query context Query suggestion LM LSA Query expansion 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Btihal El Ghali
    • 1
    Email author
  • Abderrahim El Qadi
    • 2
  • Mohamed Ouadou
    • 1
  • Driss Aboutajdine
    • 1
  1. 1.LRIT Associated Unit to the CNRST - URAC N°29 Faculty of ScienceMohammed V- UniversityRabatMorocco
  2. 2.TIMHigh School of Technology Moulay Ismaïl UniversityMeknesMorocco

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