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CICLING
2009
Springer
14 years 5 months ago
Semi-supervised Clustering for Word Instances and Its Effect on Word Sense Disambiguation
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...
Kazunari Sugiyama, Manabu Okumura
COLING
2002
13 years 5 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
CORR
2004
Springer
125views Education» more  CORR 2004»
13 years 5 months ago
Word Sense Disambiguation by Web Mining for Word Co-occurrence Probabilities
This paper describes the National Research Council (NRC) Word Sense Disambiguation (WSD) system, as applied to the English Lexical Sample (ELS) task in Senseval-3. The NRC system ...
Peter D. Turney
COLING
2008
13 years 6 months ago
Word Sense Disambiguation for All Words using Tree-Structured Conditional Random Fields
We propose a supervised word sense disambiguation (WSD) method using tree-structured conditional random fields (TCRFs). By applying TCRFs to a sentence described as a dependency t...
Jun Hatori, Yusuke Miyao, Jun-ichi Tsujii
ACL
2008
13 years 6 months ago
Choosing Sense Distinctions for WSD: Psycholinguistic Evidence
Supervised word sense disambiguation requires training corpora that have been tagged with word senses, which begs the question of which word senses to tag with. The default choice...
Susan Windisch Brown