138 search results - page 1 / 28 » Improving Word Sense Disambiguation Using Topic Features |
EMNLP
2007
13 years 6 months ago
2007
This paper presents a novel approach for exploiting the global context for the task of word sense disambiguation (WSD). This is done by using topic features constructed using the ...
EMNLP
2007
13 years 6 months ago
2007
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
COLING
2008
13 years 6 months ago
2008
The use of topical features is abundant in Natural Language Processing (NLP), a major example being in dictionary-based Word Sense Disambiguation (WSD). Yet previous research does...
ACL
2010
13 years 2 months ago
2010
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...
CICLING
2009
Springer
14 years 5 months ago
2009
Springer
We propose a supervised word sense disambiguation (WSD) system that uses features obtained from clustering results of word instances. Our approach is novel in that we employ semi-s...