Difference between revisions of "Smith and Eisner 2005:Contrastive Estimation: Training Log-Linear Models on Unlabeled Data"
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== Summary == | == Summary == | ||
− | This is a crucial [[Category::paper]] that presents an unsupervised estimation method to [[AddressesProblem::Part of Speech Tagging]]. | + | This is a crucial [[Category::paper]] that presents an unsupervised estimation method for [[UsesMethod::Conditional Random Fields]], which can be easily applied to problems like [[AddressesProblem::Part of Speech Tagging]]. |
== Brief description of the method == | == Brief description of the method == |
Revision as of 14:55, 27 September 2011
Contents
Citation
Smith, Noah A. and Jason Eisner (2005). Contrastive estimation: Training log-linear models on unlabeled data. Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 354-362, Ann Arbor, Michigan, June.
Online version
Summary
This is a crucial paper that presents an unsupervised estimation method for Conditional Random Fields, which can be easily applied to problems like Part of Speech Tagging.