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UC Berkeley at CLEF-2003 – Russian Language Experiments and Domain-Specific Retrieval

  • Vivien Petras
  • Natalia Perelman
  • Fredric Gey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3237)

Abstract

As in the previous years, Berkeley’s group 1 experimented with the domain-specific CLEF collection GIRT as well as with Russian as query and document language. The GIRT collection was substantially extended this year and we were able to improve our retrieval results for the query languages German, English and Russian. For the GIRT retrieval experiments, we utilized our previous experiences by combining different translations, thesaurus matching, decompounding for German compounds and a blind feedback algorithm. We find that our thesaurus matching technique compares to conventional machine translation for Russian and German against English retrieval and outperforms machine translation for English to German retrieval.

With the introduction of a Russian document collection in CLEF 2003, we participated in the CLEF main task with monolingual and bilingual runs for the Russian collection. For bilingual retrieval our approaches were query translation (for German or English as topic languages) and document translation (for English as the topic language). Document translation significantly underperformed query translation (using the Promt translation system).

Keywords

Machine Translation Query Language Retrieval Result Machine Translation System Query Translation 
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 2004

Authors and Affiliations

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

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