Special section: Information Retrieval and Natural Language Processing

 

Using Sense Clustering for the Disambiguation of Words

 

Henry Anaya–Sánchez¹, Aurora Pons–Porrata¹, and Rafael Berlanga–Llavori²

 

¹ Center for Pattern Recognition and Data Mining, Universidad de Oriente, Santiago de Cuba, Cuba. (henry@cepramid.co.cu, aurora@cepramid.co.cu).

² Department of Langauges and Computer Systems, Universitat Jaume I, Castello, Spain. (berlanga@lsi.uji.es).

 

Manuscript received November 4, 2008.
Manuscript accepted for publication August 28, 2009.

 

Abstract

Clustering methods have been extensively used in the solution of many Information Processing tasks in order to capture unknown object categories. This paper presents an approach to Word Sense Disambiguation based on clustering. The underlying idea is that the clustering of word senses provides a useful way to discover semantically related senses. We evaluate our proposal regarding both fine– and coarse–grained disambiguation. Experimental results over Senseval–3 all–words, SemCor 2.0 and SemEval–2007 corpora are presented. Promising values of precision and recall are obtained.

Key words: Word sense disambiguation, clustering.

 

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