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]].  
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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

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

Smith and Eisner 2005

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.

Brief description of the method

Experimental Result

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