Exemplar-Based Word Sense Disambiguation: Some Recent Improvements
| dc.creator | Ng, Hwee Tou | |
| dc.date | 1997-06-10 | |
| dc.date.accessioned | 2026-07-07T09:10:50Z | |
| dc.date.available | 2026-07-07T09:10:50Z | |
| dc.description | In this paper, we report recent improvements to the exemplar-based learning approach for word sense disambiguation that have achieved higher disambiguation accuracy. By using a larger value of $k$, the number of nearest neighbors to use for determining the class of a test example, and through 10-fold cross validation to automatically determine the best $k$, we have obtained improved disambiguation accuracy on a large sense-tagged corpus first used in \cite{ng96}. The accuracy achieved by our improved exemplar-based classifier is comparable to the accuracy on the same data set obtained by the Naive-Bayes algorithm, which was reported in \cite{mooney96} to have the highest disambiguation accuracy among seven state-of-the-art machine learning algorithms. | |
| dc.description | 6 pages | |
| dc.identifier | https://arxiv.org/abs/cmp-lg/9706010 | |
| dc.identifier | http://arxiv.org/abs/cmp-lg/9706010 | |
| dc.identifier | In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing (EMNLP-2), August 1997 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/151473 | |
| dc.subject | Computation and Language | |
| dc.title | Exemplar-Based Word Sense Disambiguation: Some Recent Improvements | |
| dc.type | text |