“School of Cognitive”
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| Paper IPM / Cognitive / 9584 |
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Word Sense Disambiguation (WSD) aims to identify the correct sense of an ambiguous word in a sentence. In this work we investigate the performance of two state-of-the art approaches: k-NN and Na�ve Bayes for the purpose of Persian word sense disambiguation. These methods have been evaluated on two highly frequent and ambiguous words from ?Hamshahri?- by some means a standard corpus for Persian language. We performed experiments on both stemmed and non-stemmed version of the corpus. The results show the superiority of k-NN algorithm over Na�ve Bayes in almost all cases. Although the results demonstrate good performance, further investigation should be done, by trying other classification methods and also other features used in the literature.
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