Identifying concepts on specific domain by a unsupervised graph-based approach

Abstract

This paper presents an unsupervised approach to Word Sense Disambiguation on a specific domain to automatically to assign the right sense to a given ambiguous word. The approach proposed relies on integration of two source information: context and semantic similarity information. The experiments were carried on English test data of SemEval 2010 and evaluated with a variety of measures that analyze the connectivity of graph structure. The obtained result were evaluated using precision and recall measures and compared with the results of SemEval 2010 the approach is currently under test with another semantic similarity measures, preliminary results look promising. © 2012 Springer-Verlag.