Performance analysis of recent Word Sense Disambiguation techniques

Abstract

This paper presents recent advances in the in the area of Word Sense Disambiguation (WSD). While the supervised machine learning techniques have proven to be most efficient with the problem of availability of sense tagged data. While describing a few important techniques the paper then represents a comparative analysis among them. There is very less commonality among the data sets which have been used but it has been found out that the Genetic Algorithm based approach has the capability to beat other milestone techniques in the literature.