Chapter

Advances in Artificial Intelligence - IBERAMIA-SBIA 2006

Volume 4140 of the series Lecture Notes in Computer Science pp 472-481

Word Sense Disambiguation Based on Word Sense Clustering

  • Henry Anaya-SánchezAffiliated withCarnegie Mellon UniversityCenter of Pattern Recognition and Data Mining, Universidad de Oriente
  • , Aurora Pons-PorrataAffiliated withCarnegie Mellon UniversityCenter of Pattern Recognition and Data Mining, Universidad de Oriente
  • , Rafael Berlanga-LlavoriAffiliated withCarnegie Mellon UniversityUniversitat Jaume I

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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.