Unsupervised Word Sense Disambiguation Using Collocation and Measures of Graph Connectivity
Jung Gil Cho · International Journal of Software Engineering and Its Applications · 2015
Word Sense Disambiguation has been selected as research objectives in natural language processing for a long time, and it is a necessary task used to identify word senses in context. This paper explains the unsupervised graph-based WSD approach and suggests a new WSD approach using collocation and measures of graph connectivity. This approach uses collocation to find the accurate word sense in context, and searches words sense by measuring graph connectivity when the word can’t be found with collocation. The performance evaluation on the standard data set indicates that it has enhanced accuracy compared to the many existing graph-based algorithms.