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» Similarity-Based Methods for Word Sense Disambiguation
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COLING
2002
14 years 11 months ago
A Maximum Entropy-based Word Sense Disambiguation System
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
Armando Suárez, Manuel Palomar
EMNLP
2007
15 years 1 months ago
Improving Word Sense Disambiguation Using Topic Features
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 ...
Junfu Cai, Wee Sun Lee, Yee Whye Teh
COLING
2008
15 years 1 months ago
On Robustness and Domain Adaptation using SVD for Word Sense Disambiguation
In this paper we explore robustness and domain adaptation issues for Word Sense Disambiguation (WSD) using Singular Value Decomposition (SVD) and unlabeled data. We focus on the s...
Eneko Agirre, Oier Lopez de Lacalle
BMCBI
2006
151views more  BMCBI 2006»
14 years 11 months ago
Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues
Background: Word sense disambiguation (WSD) is critical in the biomedical domain for improving the precision of natural language processing (NLP), text mining, and information ret...
Hua Xu, Marianthi Markatou, Rositsa Dimova, Hongfa...
ACL
1994
15 years 1 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