Word sense disambiguation (WSD) systems based on supervised learning achieved the best performance in SensEval and SemEval workshops. However, there are few publicly available ope...
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. We describe a system which t)erforms word sense disambiguation on al...
This paper presents Domain Relevance Estimation (DRE), a fully unsupervised text categorization technique based on the statistical estimation of the relevance of a text with respe...
This paper describes the National Research Council (NRC) Word Sense Disambiguation (WSD) system, as applied to the English Lexical Sample (ELS) task in Senseval-3. The NRC system ...
The degree of dominance of a sense of a word is the proportion of occurrences of that sense in text. We propose four new methods to accurately determine word sense dominance using...