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“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 9584
School of Cognitive Sciences
  Title:   Persian Word Sense Disambiguation
  Author(s): 
1.  Mandana Hamidi
2.  Ali Borji
3.  Saeed Shiry Ghidary
  Status:   In Proceedings
  Proceeding: Proceeding of 15th Iranian Conference of Electrical and Electronics Engineers (ICEE 2007)
  Year:  2007
  Supported by:  IPM
  Abstract:
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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