Title of article :
Word Sense Disambiguation Based on Lexical and Semantic FeaturesUsing Naive Bayes Classifier
Author/Authors :
Rasekh، Amir Hossein نويسنده Computer Science and Engineering Department, Shiraz, Iran. , , Mohammad Hadi Sadreddini، Mohammad Hadi Sadreddini نويسنده Department of Computer Science and Eng. and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran Mohammad Hadi Sadreddini, Mohammad Hadi Sadreddini , Fakhrahmad، Seyed Mostafa نويسنده Computer Science and Engineering Department, Shiraz, Iran. ,
Issue Information :
فصلنامه با شماره پیاپی 0 سال 2014
Pages :
10
From page :
123
To page :
132
Abstract :
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.
Journal title :
Journal of Computing and Security
Serial Year :
2014
Journal title :
Journal of Computing and Security
Record number :
1518176
Link To Document :
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