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IR-n in the CLEF Robust WSD Task 2008

  • Sergio Navarro
  • Fernando Llopis
  • Rafael Muñoz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

In our approach to the Robust WSD task we have used a passage based system jointly with a WordNet and WSD based term expansion for the documents and queries. Furthermore, we have experimented with two well known relevance feedback methods - LCA and PRF -, in order to figure out which is more suitable to take profit of the WSD query expansion based on Wordnet. Our best run has obtained a 4th - 0.4008 MAP -. A major finding is that LCA fits better than PRF to this task due to it is able to take advantage of the expanded documents and queries.

Keywords

Relevance Feedback Query Expansion Word Sense Disambiguation Polysemous Word Pseudo Relevance Feedback 
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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References

  1. 1.
    Agirre, E., Di Nunzio, G.M., Ferro, N., Mandl, T., Peters, C.: CLEF 2008: Ad Hoc track overview. In: Peters, C., et al. (eds.) CLEF 2008. LNCS, vol. 5706, pp. 15–37. Springer, Heidelberg (2009)Google Scholar
  2. 2.
    Llopis, F.: IR-n: Un Sistema de Recuperacin de Informacin Basado en Pasajes. PhD thesis, University of Alicante (2003)Google Scholar
  3. 3.
    Robertson, S.E., Sparck Jones, K.: Relevance weighting of search terms. Journal of the American Society for Information Science 27(3), 129–146 (1976)CrossRefGoogle Scholar
  4. 4.
    Xu, J., Croft, W.B.: Improving the effectiveness of information retrieval with local context analysis. ACM Trans. Inf. Syst. 18(1), 79–112 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sergio Navarro
    • 1
  • Fernando Llopis
    • 1
  • Rafael Muñoz
    • 1
  1. 1.Natural Language Processing and Information Systems GroupUniversity of AlicanteSpain

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