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 ...
This paper presents a method for the resolution of lexical ambiguity of nouns and its automatic evaluation over the Brown Corpus. The method relies on the use of the wide-coverage...
This paper presents a probabilistic model for sense disambiguation which chooses the best sense based on the conditional probability of sense paraphrases given a context. We use a...
It is popular in WSD to use contextual information in training sense tagged data. Co-occurring words within a limited window-sized context support one sense among the semantically...
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...