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COLING
2000
14 years 11 months ago
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
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...
Gerald Chao, Michael G. Dyer
ACL
2010
14 years 7 months ago
Topic Models for Word Sense Disambiguation and Token-Based Idiom Detection
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...
Linlin Li, Benjamin Roth, Caroline Sporleder
ACL
1994
14 years 11 months ago
Word-Sense Disambiguation Using Decomposable Models
Most probabilistic classi ers used for word-sense disambiguationhave either been based on onlyone contextual feature or have used a model that is simply assumed to characterize th...
Rebecca F. Bruce, Janyce Wiebe
EMNLP
2007
14 years 11 months ago
A Topic Model for Word Sense Disambiguation
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...
Jordan L. Boyd-Graber, David M. Blei, Xiaojin Zhu
COLING
1990
14 years 10 months ago
Word Sense Disambiguation with Very Large Neural Networks Extracted from Machine Readable Dictionaries
In this paper, we describe a means for automatically building very large neural networks (VLNNs) from definition texts in machine-readable dictionaries, and demonstrate the use of...
Jean Véronis, Nancy Ide