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FGCN
2008
IEEE
130views Communications» more  FGCN 2008»
13 years 11 months ago
Word Sense Disambiguation Based on Bayes Model and Information Gain
Word sense disambiguation has always been a key problem in Natural Language Processing. In the paper, we use the method of Information Gain to calculate the weight of different po...
Zhengtao Yu, Bin Deng, Bo Hou, Lu Han, Jianyi Guo
ACL
2008
13 years 6 months ago
An Unsupervised Vector Approach to Biomedical Term Disambiguation: Integrating UMLS and Medline
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...
Bridget McInnes
AAAI
2006
13 years 6 months ago
Kernel Methods for Word Sense Disambiguation and Acronym Expansion
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
LREC
2010
202views Education» more  LREC 2010»
13 years 6 months ago
Can Syntactic and Logical Graphs help Word Sense Disambiguation?
This paper presents a word sense disambiguation (WSD) approach based on syntactic and logical representations. The objective here is to run a number of experiments to compare stan...
Amal Zouaq, Michel Gagnon, Benoît Ozell
COLING
2008
13 years 6 months ago
Using Three Way Data for Word Sense Discrimination
In this paper, an extension of a dimensionality reduction algorithm called NONNEGATIVE MATRIX FACTORIZATION is presented that combines both `bag of words' data and syntactic ...
Tim Van de Cruys