Word Sense Disambiguation Based on Lexical and Semantic Features Using Naive Bayes Classifier


1 Shiraz University

2 Computer Science and Engineering Department, Shiraz, Iran.


Machine translation is considered as a branch of machine intelligence with about fifty years background. Ambiguity of language is the most problematic issue in machine translation systems, which may lead to unclear or wrong translation. One of the problems involved in natural language processing is the semantic and structural ambiguity of the words. The objective of this paper to focused on the word sense disambiguation. In here, the existing algorithms for word sense disambiguation are evaluated and a method which is proposed based on the concept, structure and meaning of the words. The experimental results are promising and indicate that this proposed approach significantly outperform its counterparts in terms of disambiguation accuracy.


Volume 1, Issue 2 - Serial Number 2
April 2014
Pages 123-132
  • Receive Date: 28 January 2013
  • Revise Date: 26 May 2018
  • Accept Date: 25 September 2017
  • First Publish Date: 25 September 2017