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Abstract

JHU/APL continued its participation in multilingual retrieval at CLEF in 2006. We again applied our hallmark technique for combating language diversity and morphological complexity: character n-gram tokenization. This year we participated in the ad hoc cross-language track and submitted both monolingual and bilingual runs. Our experimental results this year agree with our previous reports that n-grams perform especially well in linguistically complex languages, notably Bulgarian and Hungarian, where monolingual improvements of 27% and 70% respectively were observed compared to space-delimited word forms. As in CLEF 2005, our bilingual submissions made use of subword translation, statistical translation of character n-grams using aligned corpora, when parallel data were available, and web-based machine translation, when no suitable data was available to us.

Keywords

Cross-language information retrieval character n-gram tokenization corpus-based translation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Paul McNamee
    • 1
  1. 1.Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD 20723-6099USA

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