Smith and Eisner 2005:Contrastive Estimation: Training Log-Linear Models on Unlabeled Data
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.
This is an interesting paper that presents an unsupervised Contrastive Estimation method for Conditional Random Fields and other Log-Linear Models, which can be easily applied to problems like Part of Speech Tagging, Part of Speech Tagging and 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.