Monolingual, Bilingual, and GIRT Information Retrieval at CLEF-2005

  • Jacques Savoy
  • Pierre-Yves Berger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


For our fifth participation in the CLEF evaluation campaigns, our first objective was to propose an effective and general stopword list as well as a light stemming procedure for the Hungarian, Bulgarian and Portuguese (Brazilian) languages. Our second objective was to obtain a better picture of the relative merit of various search engines when processing documents in those languages. To do so we evaluated our scheme using two probabilistic models and five vector-processing approaches. In the bilingual track, we evaluated both the machine translation and bilingual dictionary approaches applied to automatically translate a query submitted in English into various target languages. Finally, using the GIRT corpora (available in English, German and Russian), we investigated the variations in retrieval effectiveness that resulted when we included or excluded manually assigned keywords attached to the bibliographic records (mainly comprising a title and an abstract).


Machine Translation Average Precision Retrieval Performance Bibliographic Record Translation Tool 
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

  • Jacques Savoy
    • 1
  • Pierre-Yves Berger
    • 1
  1. 1.Institut interfacultaire d’informatiqueUniversité de NeuchâtelNeuchâtelSwitzerland

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