Combining Classifiers with Multi-representation of Context in Word Sense Disambiguation

  • Cuong Anh Le
  • Van-Nam Huynh
  • Akira Shimazu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3518)


In this paper, we first argue that various ways of using context in WSD can be considered as distinct representations of a polysemous word under consideration, then all these representations are used jointly to identify the meaning of the target word. Under such a consideration, we can then straightforwardly apply the general framework for combining classifiers developed in Kittler et al. [5] to WSD problem. This results in many commonly used decision rules for WSD. The experimental result shows that the multi-representation based combination strategy of classifiers outperform individual ones as well as known techniques of classifier combination in WSD.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Cuong Anh Le
    • 1
    • 3
  • Van-Nam Huynh
    • 2
  • Akira Shimazu
    • 1
  1. 1.School of Information ScienceJapan Advanced Institute of Science and TechnologyTatsunokuchi, IshikawaJapan
  2. 2.School of Knowledge ScienceJapan Advanced Institute of Science and TechnologyTatsunokuchi, IshikawaJapan
  3. 3.College of TechnologyVietnam National University, HanoiHanoiVietnam

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