Word Sense Disambiguation Based on Word Sense Clustering

  • Henry Anaya-Sánchez
  • Aurora Pons-Porrata
  • Rafael Berlanga-Llavori
Conference paper

DOI: 10.1007/11874850_51

Volume 4140 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Anaya-Sánchez H., Pons-Porrata A., Berlanga-Llavori R. (2006) Word Sense Disambiguation Based on Word Sense Clustering. In: Sichman J.S., Coelho H., Rezende S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. Lecture Notes in Computer Science, vol 4140. Springer, Berlin, Heidelberg

Abstract

In this paper we address the problem of Word Sense Disambiguation by introducing a knowledge-driven framework for the disambiguation of nouns. The proposal is based on the clustering of noun sense representations and it serves as a general model that includes some existing disambiguation methods. A first prototype algorithm for the framework, relying on both topic signatures built from WordNet and the Extended Star clustering algorithm, is also presented. This algorithm yields encouraging experimental results for the SemCor corpus, showing improvements in recall over other knowledge-driven methods.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Henry Anaya-Sánchez
    • 1
  • Aurora Pons-Porrata
    • 1
  • Rafael Berlanga-Llavori
    • 2
  1. 1.Center of Pattern Recognition and Data MiningUniversidad de OrienteCuba
  2. 2.Universitat Jaume ICastellónSpain