In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Abstract. This paper describes a novel method for a word sense disambiguation that utilizes relatives (i.e. synonyms, hypernyms, meronyms, etc in WordNet) of a target word and raw ...
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...
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 ...
Word sense disambiguation is the task to identify the intended meaning of an ambiguous word in a certain context, one of the central problems in natural language processing. This p...