700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ ReadersThis Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Research Article Open Access
Word Sense Disambiguation is a difficult task to perform in Natural Language Processing and it is the process of identifying the correct sense or correct meaning about a word. This is basically used in application like information retrieval, machine translation, information extraction because of its semantics understanding. There are various methods available in supervised approach to perform the disambiguaty of word. This papers described a Na?ve Bayes method of Supervised Learning Approach which is based on probabilistic method. The main emphasis of this paper is feature selection for disambiguation purpose. Here we have just tried to remove the stop words while selecting the feature set.