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EMNLP
2004
15 years 1 months ago
Unsupervised WSD based on Automatically Retrieved Examples: The Importance of Bias
This paper explores the large-scale acquisition of sense-tagged examples for Word Sense Disambiguation (WSD). We have applied the "WordNet monosemous relatives" method t...
Eneko Agirre, David Martínez
IRCDL
2007
15 years 1 months ago
An Hybrid Approach for Improving Word Sense Disambiguation and Text Clustering
Abstract— In this paper we suggest a new approach to represent text document collections, integrating background knowledge to improve clustering effectiveness. Background knowled...
Paolo Casoto, Carlo Tasso
EMNLP
2007
15 years 1 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
BMCBI
2010
186views more  BMCBI 2010»
14 years 11 months ago
Knowledge-based biomedical word sense disambiguation: comparison of approaches
Background: Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be u...
Antonio Jimeno Yepes, Alan R. Aronson
TAL
2010
Springer
14 years 10 months ago
Robust Semi-supervised and Ensemble-Based Methods in Word Sense Disambiguation
Mihalcea [1] discusses self-training and co-training in the context of word sense disambiguation and shows that parameter optimization on individual words was important to obtain g...
Anders Søgaard, Anders Johannsen