Concept-based Word Sense Disambiguation for Information Retrieval System

Abstract

Word sense disambiguation (WSD) is an important technique for many NLP applications such as machine translation, content analysis and information retrieval. In the information retrieval (IR) system, ambiguous words are damaging effect on the precision of this system. In this situation, WSD process is useful for automatically identifying the correct meaning of an ambiguous word. Therefore, this system proposes the optimal concept-based word sense disambiguation algorithm to increase the precision of the IR system about technology domain. This system provides additional semantics as conceptually related words with the help of glosses to each keyword in the documents by disambiguating their meanings. This system uses the WordNet as the lexical resource that encodes concepts of each term. In this system, various senses that are provided by concept-based WSD algorithm have been used as semantics for indexing the documents to improve performance of IR system. This system is implemented by using C# programming language.