An experiment in computational discrimination of English word senses
IBM Journal of Research and Development
C4.5: programs for machine learning
C4.5: programs for machine learning
SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Machine Learning
Machine Learning
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Disambiguating highly ambiguous words
Computational Linguistics - Special issue on word sense disambiguation
Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Lexical disambiguation using simulated annealing
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 1
Word-sense disambiguation using statistical models of Roget's categories trained on large corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Genus disambiguation: a study in weighted preference
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 4
Corpus-based statistical sense resolution
HLT '93 Proceedings of the workshop on Human Language Technology
Learning rules for large vocabulary word sense disambiguation
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
A mapping between classifiers and training conditions for WSD
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Mining class association rules for word sense disambiguation
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
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In this article we compare the performance of various machine learning algorithms on the task of constructing word-sense disambiguation rules from data. The distinguishing characteristic of our work from most of the related work in the field is that we aim at the disambiguation of all content words in the text, rather than focussing on a small number of words. In an earlier study we have shown that a decision tree induction algorithm performs well on this task. This study compares decision tree induction with other popular learning methods and discusses their advantages and disadvantages. Our results confirm the good performance of decision tree induction, which outperforms the other algorithms, due to its ability to order the features used for disambiguation, according to their contribution in assigning the correct sense.