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Multi-language Models and Meta-dictionary Adaptation for Accessing Multilingual Digital Libraries

  • Stephane Clinchant
  • Jean-Michel Renders
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

Accessing digital libraries raises the important issue of how to deal with the multilinguality of the documents. Inside a target collection, documents can be written in very different languages and the record associated to a particular document often contains field descriptors in different languages. This paper proposes a principled way to solve this issue, by proposing a multi-language model approach to information retrieval, as well as an extension of the dictionary adaptation mechanism to cover multiple languages (including the source language). In experiments related to the TEL task of the CLEF2008 Ad-hoc track, runs based on the assumption of a purely bilingual approach, translating the query only in the official language of the collection, appeared to result in performance (mean average precision) larger or equal to the ones of the other participants. But, contrarily to our initial intuition, in the case of the TEL task, the experiments showed that exploiting information in languages different from the official language of the collection turns out to offer no advantage.

Keywords

Language Model Digital Library Average Precision Source Language Late Fusion 
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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References

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    Clinchant, S., Renders, J.-M.: Xrce’s participation to clef 2008 ad-hoc track. In: Working Notes of CLEF 2008. Avalaible On-line on the CLEF Web Site (2008)Google Scholar
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Stephane Clinchant
    • 1
  • Jean-Michel Renders
    • 1
  1. 1.Xerox Research Centre EuropeFrance

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