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CD-ARES 2012: Multidisciplinary Research and Practice for Information Systems pp 244–258Cite as

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Integrating Query Context and User Context in an Information Retrieval Model Based on Expanded Language Modeling

Integrating Query Context and User Context in an Information Retrieval Model Based on Expanded Language Modeling

  • Rachid Aknouche21,
  • Ounas Asfari21,
  • Fadila Bentayeb21 &
  • …
  • Omar Boussaid21 
  • Conference paper
  • 2126 Accesses

  • 5 Citations

  • 7 Altmetric

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7465)

Abstract

Access to relevant information adapted to the needs and the context of the user is a real challenge. The user context can be assimilated to all factors that can describe his intentions and perceptions of his surroundings. It is difficult to find a contextual information retrieval system that takes into account all contextual factors. In this paper, both types of context user context and query context are integrated in an Information Retrieval (IR) model based on language modeling. Here, the query context include the integration of linguistic and semantic knowledge about the user query in order to explore the most exact understanding of user’s information needs. In addition, we consider one of the important factors of the user context, the user’s domain of interest or the interesting topic. A thematic algorithm is proposed to describe the user context. We assume that each topic can be characterized by a set of documents from the experimented corpus. The documents of each topic are used to build a statistical language model, which is then integrated to expand the original query model and to re-rank the retrieved documents. Our experiments on the 20_Newsgroup corpus show that the proposed contextual approach improves significantly the retrieval effectiveness compared to the basic approach, which does not consider contextual factors.

Keywords

  • Information Retrieval
  • Language Model
  • Query Expansion
  • User Query
  • Semantic Knowledge

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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Author information

Authors and Affiliations

  1. ERIC Laboratory, (Equipe de Recherche en Ingnierie des Connaissances), 5 Avenue Pierre Mends France, 69676, Bron Cedex, France

    Rachid Aknouche, Ounas Asfari, Fadila Bentayeb & Omar Boussaid

Authors
  1. Rachid Aknouche
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  2. Ounas Asfari
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  3. Fadila Bentayeb
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  4. Omar Boussaid
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Editor information

Editors and Affiliations

  1. Department of IT, Engineering and Environment, University of South Australia, Mawson Lakes Campus, 5001, Adelaide, SA, Australia

    Gerald Quirchmayr

  2. Department of Information Technologies, University of Economics, W. Churchill Sq. 4, 130 67, Prague 3, Czech Republic

    Josef Basl

  3. School of Information Science, Korean Bible University, 16 Danghyun 2-gil, Nowon-gu, 139-791, Seoul, Korea

    Ilsun You

  4. Information Technology and Decision Sciences, Old Dominion University, 2076 Constant Hall, 23529, Norfolk, VA, USA

    Lida Xu

  5. Institute of Software Technology and Interactive Systems, Vienna University of Technology and SBA Research, Favoritenstrsse 9-11, 1040, Vienna, Austria

    Edgar Weippl

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© 2012 IFIP International Federation for Information Processing

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Cite this paper

Aknouche, R., Asfari, O., Bentayeb, F., Boussaid, O. (2012). Integrating Query Context and User Context in an Information Retrieval Model Based on Expanded Language Modeling. In: Quirchmayr, G., Basl, J., You, I., Xu, L., Weippl, E. (eds) Multidisciplinary Research and Practice for Information Systems. CD-ARES 2012. Lecture Notes in Computer Science, vol 7465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32498-7_19

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  • DOI: https://doi.org/10.1007/978-3-642-32498-7_19

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