The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Automatic word sense discrimination
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
Word-sense disambiguation using decomposable models
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Corpus-based statistical sense resolution
HLT '93 Proceedings of the workshop on Human Language Technology
Boosting Applied toe Word Sense Disambiguation
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Multi-resolution disambiguation of term occurrences
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
An empirical assessment of semantic interpretation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Verb class disambiguation using informative priors
Computational Linguistics
Development and use of a gold-standard data set for subjectivity classifications
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Unsupervised Italian word sense disambiguation using WordNets and unlabeled corpora
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
Training a naive bayes classifier via the EM algorithm with a class distribution constraint
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Ontology learning: state of the art and open issues
Information Technology and Management
International Journal of Data Mining and Bioinformatics
International Journal of Data Mining and Bioinformatics
Adjective Sense Disambiguation at the Border Between Unsupervised and Knowledge-Based Techniques
Fundamenta Informaticae
Discriminating among word meanings by identifying similar contexts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Artificial Intelligence Review
Classification of Dreams Using Machine Learning
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
State of the art versus classical clustering for unsupervised word sense disambiguation
Artificial Intelligence Review
Adjective Sense Disambiguation at the Border Between Unsupervised and Knowledge-Based Techniques
Fundamenta Informaticae
Fundamenta Informaticae - Emergent Computing
Unsupervised word sense disambiguation with N-gram features
Artificial Intelligence Review
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We present a corpus-based approach to word-sense disambiguation that only requires information that can be automatically extracted from untagged text. We use unsupervised techniques to estimate the parameters of a model describing the conditional distribution of the sense group given the known contextual features. Both the EM algorithm and Gibbs Sampling are evaluated to determine which is most appropriate for our data. We compare their disambiguation accuracy in an experiment with thirteen different words and three feature sets. Gibbs Sampling results in small but consistent improvement in disambiguation accuracy over the EM algorithm.