International Journal of Advances in Computer Science and Its Applications
Author(s) : FARAZ HASAN, MOHAMMAD UBAIDULLAH BOKHARI, SYED HAMID HASAN
Word Sense Disambiguation (WSD) is one of the core challenging area for researchers since several decades and it plays a crucial role in all natural language processing (NLP) applications viz. Information Retrieval, Information Extraction, Question Answering, Text Mining, Machine Translation etc. Researchers defined WSD as to identify the actual meaning of a word based on the context in which it occurs. Whereas in linguistic, context is defined as the text in which a word or passage appears and which helps ascertain its meaning. Hence, context of a word depends on different part of speech (POS) of a sentence i.e. Noun, Verb, pronoun, adjective and adverb. This paper proposes a novel approach for context based word sense disambiguation using soft sense disambiguation, map-reduce, knowledge based multimodal algorithm and WordNet.