We introduce a new method for disambiguating word senses that exploits a nonlinear Kernel Principal Component Analysis (KPCA) technique to achieve accuracy superior to the best pu...
This paper introduces an unsupervised vector approach to disambiguate words in biomedical text that can be applied to all-word disambiguation. We explore using contextual informat...
Abstract. This paper describes our approach to the Question Answering - Word Sense Disambiguation task. This task consists in carrying out Question Answering over a disambiguated d...
In this paper Schapire and Singer's AdaBoost.MH boosting algorithm is applied to the Word Sense Disambiguation (WSD) problem. Initial experiments on a set of 15 selected polys...
Most probabilistic classi ers used for word-sense disambiguationhave either been based on onlyone contextual feature or have used a model that is simply assumed to characterize th...