iCLEF 2003 at Maryland: Translation Selection and Document Selection

  • Bonnie Dorr
  • Daqing He
  • Jun Luo
  • Douglas W. Oard
  • Richard Schwartz
  • Jianqiang Wang
  • David Zajic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3237)

Abstract

Maryland performed two sets of experiments for the 2003 Cross-Language Evaluation Forum’s interactive track, one focused on interactive selection of appropriate translations for query terms, the second focused on interactive selection of relevant documents. Translation selection was supported using possible synonyms discovered through back translation and two techniques for generating KeyWord In Context (KWIC) examples of usage. The results indicate that searchers typically achieved a similar search effectiveness using fewer query iterations when interactive translation selection was available. For document selection, a complete extract of the first 40 words of each news story was compared to a compressed extract generated using an automated parse-and-trim approach that approximates one way in which people can produce headlines. The results indicate that compressed “headlines” result in faster assessment, but with a 20% relative reduction in the Fα= 0.8 search effectiveness measure.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Bonnie Dorr
    • 1
  • Daqing He
    • 1
  • Jun Luo
    • 1
  • Douglas W. Oard
    • 1
  • Richard Schwartz
    • 1
  • Jianqiang Wang
    • 1
  • David Zajic
    • 1
  1. 1.Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA

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