Abstract
Due to high Semantic Ambiguity that is associated with language, Word Sense Disambiguation is an open problem of Natural Language Processing and Ontology in Computer Linguistics. For instance, the word Head can mean the part of body and a person in charge of organization. The task of automatically assigning the most suitable meaning to a polysemous word can be defined as Word Sense Disambiguation. Several approaches have been done, from Dictionary-and Knowledge-based method that uses Lexical resource like WordNet, to Supervised-Machine learning method that use trained classifier on manually sense-annotated corpus, to cluster based Un-Supervised methods. These approaches have been applied for several languages like German, English, French, Chinese, and some Indian languages like Assamese, Hindi, Marathi and Malayalam. This survey aims to present about some aspect of word sense disambiguation and its approaches, focusing more on Unsupervised Graph based approach.
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