Most word sense disambiguation (WSD) methods require large quantities of manually annotated training data and/or do not exploit fully the semantic relations of thesauri. We propos...
George Tsatsaronis, Michalis Vazirgiannis, Ion And...
We present results that show that incorporating lexical and structural semantic information is effective for word sense disambiguation. We evaluated the method by using precise in...
Takaaki Tanaka, Francis Bond, Timothy Baldwin, San...
In this paper we describe a method for performing word sense disambiguation (WSD). The method relies on unsupervised learning and exploits functional relations among words as prod...
This paper presents an algorithm to apply the smoothing techniques described in [1] to three different Machine Learning (ML) methods for Word Sense Disambiguation (WSD). The method...
Recent research presents conflicting evidence on whether word sense disambiguation (WSD) systems can help to improve the performance of statistical machine translation (MT) syste...