Recent research works on unsupervised word sense disambiguation report an increase in performance, which reduces their handicap from the respective supervised approaches for the sa...
George Tsatsaronis, Iraklis Varlamis, Kjetil N&osl...
This paper introduces an unsupervised vector approach to disambiguate words in biomedical text that can be applied to all-word disambiguation. We explore using contextual informat...
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
We apply decision tree induction to the problem of discourse clue word sense disambiguation. The automatic partitioning of the training set which is intrinsic to decision tree ind...
Word clustering is important for automatic thesaurus construction, text classification, and word sense disambiguation. Recently, several studies have reported using the web as a c...
Yutaka Matsuo, Takeshi Sakaki, Koki Uchiyama, Mits...