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Abstract

For CLEF 2008 JHU conducted monolingual and bilingual experiments in the ad hoc TEL and Persian tasks. Additionally we performed several post hoc experiments using previous CLEF ad hoc tests sets in 13 languages.

In all three tasks we explored alternative methods of tokenizing documents including plain words, stemmed words, automatically induced segments, a single selected n-gram from each word, and all n-grams from words (i.e., traditional character n-grams). Character n-grams demonstrated consistent gains over ordinary words in each of these three diverse sets of experiments. Using mean average precision, relative gains of of 50-200% on the TEL task, 5% on the Persian task, and 18% averaged over 13 languages from past CLEF evaluations, were observed.

Keywords

Average Precision Relevance Feedback Query Expansion Mean Average Precision Mean Average Precision Score 
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 2009

Authors and Affiliations

  • Paul McNamee
    • 1
  1. 1.JHU Human Language Technology Center of ExcellenceUSA

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