We propose a supervised word sense disambiguation (WSD) system that uses features obtained from clustering results of word instances. Our approach is novel in that we employ semi-s...
Abstract— In this paper we suggest a new approach to represent text document collections, integrating background knowledge to improve clustering effectiveness. Background knowled...
In this paper, we propose an automatic text classification method based on word sense disambiguation. We use “hood” algorithm to remove the word ambiguity so that each word is ...
Ying Liu, Peter Scheuermann, Xingsen Li, Xingquan ...
The use of topical features is abundant in Natural Language Processing (NLP), a major example being in dictionary-based Word Sense Disambiguation (WSD). Yet previous research does...
Word Sense Disambiguation (WSD) is an intermediate task that serves as a means to an end defined by the application in which it is to be used. However, different applications have...