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An Information-Based Cross-Language Information Retrieval Model

  • Bo Li
  • Eric Gaussier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7224)

Abstract

We present in this paper well-founded cross-language extensions of the recently introduced models in the information-based family for information retrieval, namely the LL (log-logistic) and SPL (smoothed power law) models of [4]. These extensions are based on (a) a generalization of the notion of information used in the information-based family, (b) a generalization of the random variables also used in this family, and (c) the direct expansion of query terms with their translations. We then review these extensions from a theoretical point-of-view, prior to assessing them experimentally. The results of the experimental comparisons between these extensions and existing CLIR systems, on three collections and three language pairs, reveal that the cross-language extension of the LL model provides a state-of-the-art CLIR system, yielding the best performance overall.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bo Li
    • 1
  • Eric Gaussier
    • 1
  1. 1.Laboratoire d’Informatique de Grenoble (LIG)Université J. Fourier-Grenoble 1/CNRSFrance

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