Similarity-Based Methods For Word Sense Disambiguation

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We compare four similarity-based estimation methods against back-off and maximum-likelihood estimation methods on a pseudo-word sense disambiguation task in which we controlled for both unigram and bigram frequency. The similarity-based methods perform up to 40% better on this particular task. We also conclude that events that occur only once in the training set have major impact on similarity-based estimates.
7 pages, uses psfig.tex and aclap.sty

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Computation and Language

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http://salesiana.dossiersoluciones.com/handle/123456789/151515

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cmp-lg/9708010
 http://arxiv.org/abs/cmp-lg/9708010
 Proceedings of the 35th ACL/8th EACL, pp 56--63

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arXiv