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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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. IBERAMIA SBIA 2006 2006. Lecture Notes in Computer Science(), vol 4140. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11874850_51
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DOI: https://doi.org/10.1007/11874850_51
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