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...
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...
Supervised learning methods for WSD yield better performance than unsupervised methods. Yet the availability of clean training data for the former is still a severe challenge. In ...
We present an automatic method to disambiguate the senses of the near-synonyms in the entries of a dictionary of synonyms. We combine different indicators that take advantage of th...
Abstract. The Robust-WSD at CLEF 2009 aims at exploring the contribution of Word Sense Disambiguation to monolingual and multilingual Information Retrieval. The organizers of the t...
Eneko Agirre, Giorgio Maria Di Nunzio, Thomas Mand...