Word association norms, mutual information, and lexicography
Computational Linguistics
Two languages are more informative than one
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Word-sense disambiguation using statistical methods
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
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
Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
Sequential model selection for word sense disambiguation
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
An unsupervised method for word sense tagging using parallel corpora
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Unsupervised sense disambiguation using bilingual probabilistic models
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
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This paper presents and evaluates models created according to a schema that provides a description of the joint distribution of the values of sense tags and contextual features that is potentially applicable to a wide range of content words. The models are evaluated through a series of experiments, the results of which suggest that the schema is particularly well suited to nouns but that it is also applicable to words in other syntactic categories.