In this paper, we present a new approach for word sense disambiguation (WSD) using an exemplar-based learning algorithm. This approach integrates a diverse set of knowledge source...
Graph-based methods have gained attention in many areas of Natural Language Processing (NLP) including Word Sense Disambiguation (WSD), text summarization, keyword extraction and ...
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. Thus, this work focu...
A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automati...
We determine the subjectivity of word senses. To avoid costly annotation, we evaluate how useful existing resources established in opinion mining are for this task. We show that r...