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Using Thesauri in Cross-Language Retrieval of German and French Indexed Collections

  • Vivien Petras
  • Natalia Perelman
  • Fredric Gey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2785)

Abstract

For CLEF 2002, Berkeley’s Group One experimented with Russian, French and English as query languages, and investigated thesaurus-aided retrieval for the special CLEF collections GIRT and Amaryllis. Two techniques were used to locate source language topic terms within the controlled vocabulary and replace them with the document language thesaurus terms to form the query sent against the collection index. This form of controlled vocabulary-aided translation is called thesaurus matching. Results show that thesaurus-aided cross-language retrieval performs slightly worse than machine translation retrieval on average, but can yield decidedly better results for particular queries. In addition, Berkeley submitted runs to the monolingual and bilingual (French and German) CLEF main tasks. We found that bilingual retrieval sometimes outperforms monolingual retrieval and postulate reasons to explain this phenomenon.

Keywords

Machine Translation Defense Advance Research Project Agency Stop Word List Fuzzy Match Query Topic 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Vivien Petras
    • 1
  • Natalia Perelman
    • 1
  • Fredric Gey
    • 2
  1. 1.School of Information Management and SystemsUniversity of CaliforniaBerkeleyUSA
  2. 2.UC Data Archive & Technical AssistanceUniversity of CaliforniaBerkeleyUSA

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