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CLEF2006 Question Answering Experiments at Tokyo Institute of Technology

  • E. W. D. Whittaker
  • J. R. Novak
  • P. Chatain
  • P. R. Dixon
  • M. H. Heie
  • S. Furui
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4730)

Abstract

In this paper we present the experiments performed at Tokyo Institute of Technology for the CLEF2006 Multiple Language Question Answering (QA@CLEF) track. Our approach to QA centres on a non-linguistic, data-driven, statistical classification model that uses the redundancy of the web to find correct answers. For the cross-language aspect we employed publicly available web-based text translation tools to translate the question from the source into the corresponding target language, then used the corresponding mono-lingual QA system to find the answers. The hypothesised correct answers were then projected back on to the appropriate closed-domain corpus. Correct and supported answer performance on the mono-lingual tasks was around 14% for both Spanish and French. Performance on the cross-language tasks ranged from 5% for Spanish-English, to 12% for French-Spanish. Our method of projecting answers onto documents was shown not to work well: in the worst case on the French-English task we lost 84% of our otherwise correct answers. Ignoring the need for correct support information the exact answer accuracy increased to 29% and 21% correct on the Spanish and French mono-lingual tasks, respectively.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • E. W. D. Whittaker
    • 1
  • J. R. Novak
    • 1
  • P. Chatain
    • 1
  • P. R. Dixon
    • 1
  • M. H. Heie
    • 1
  • S. Furui
    • 1
  1. 1.Dept. of Computer Science, Tokyo Institute of Technology, 2-12-1, Ookayama, Meguro-ku, Tokyo 152-8552Japan

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