A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automati...
This paper investigates conceptually and empirically the novel sense matching task, which requires to recognize whether the senses of two synonymous words match in context. We sug...
In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum entropy approach for both English and Chinese verbs. We compare the difficulty of...
Hoa Trang Dang, Ching-yi Chia, Martha Stone Palmer...
Abstract. Automated Text Categorization has reached the levels of accuracy of human experts. Provided that enough training data is available, it is possible to learn accurate autom...
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...