Knowledge-Based Contextual Overlap keen Ideas for Word Sense Disambiguation using Wordnet

Word Sense Disambiguation (WSD) is a task of identifying correct sense of a given word especially when it has multiple meanings. WSD acts as a foundation to many AI applications such as Data Mining, Information Retrieval and Machine Translation. It has drawn much interest in the last decade and much improved results are being obtained. For WSD we require a knowledge-base, using which we can resolve the ambiguity and identify the correct sense of a given word in a sentence. The most commonly used computational lexicon for WSD, especially for English, is the English Wordnet, which later inspired the use of Wordnet specifically for WSD for Indo-Aryan languages such as Hindi, Sanskrit, etc. In this paper we explore some ideas that may enhance the efficiency of knowledge-based contextual overlap WSD algorithms when they are used on Wordnets.