Correlation based Word Sense Disambiguation

Today internet usage has seen tremendous growth. As English is the primary language, documents are mostly available in English language. In India, Hindi is the prevalent language and user wants to access data in Hindi. For the language processing we are required to get the exact sense of polysemous word interpreting the meaning in a particular context. To disambiguate the meaning of the polysemous word, the techniques used is Word Sense Disambiguation (WSD). It is a known problem in natural language processing referred as lexical semantic ambiguity. In this paper, correlation analysis of context in which the target word is used with the collocation vector of definition of target word derived from Hindi WordNet i.e. developed at IIT Bombay and the co-occurrence vector which is derived from Hindi Corpus is computed. The proposed approach uses collocation information, co-occurrence information of target word to assign weights to the different senses of ambiguous word. The evaluation is done on the 60 ambiguous words, precision obtained is 88.92%. The proposed experiment shows better efficiency.