Smith and Eisner 2005:Contrastive Estimation: Training Log-Linear Models on Unlabeled Data

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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


This is an interesting paper that presents an unsupervised Contrastive Estimation method for Conditional Random Fields, which can be easily applied to problems like Part of Speech Tagging. When applying this technique to POS tagging, the observed results outperforms EM, and is robust when the dictionary quality is poor.

Brief description of the method

Experimental Result

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