The problem of the resolution of the lexical ambiguity, which is commonly referred as Word Sense Disambiguation (WSD), seems to be stuck because of the knowledge acquisition bottle...
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...
This paper presents an algorithm for unsupervised noun sense induction, based on clustering of Web search results. The algorithm does not utilize labeled training instances or any...
Goldee Udani, Shachi Dave, Anthony Davis, Tim Sibl...
This paper presents and evaluates models created according to a schema that provides a description of the joint distribution of the values of sense tags and contextual features th...
In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. The pro...
Diana McCarthy, Rob Koeling, Julie Weeds, John A. ...