Date of Original Version

6-2010

Type

Conference Proceeding

Journal Title

Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

First Page

733

Last Page

736

Rights Management

Copyright 2010 ACL

Abstract or Description

We describe a method of incorporating taskspecific cost functions into standard conditional log-likelihood (CLL) training of linear structured prediction models. Recently introduced in the speech recognition community, we describe the method generally for structured models, highlight connections to CLL and max-margin learning for structured prediction (Taskar et al., 2003), and show that the method optimizes a bound on risk. The approach is simple, efficient, and easy to implement, requiring very little change to an existing CLL implementation. We present experimental results comparing with several commonly-used methods for training structured predictors for named-entity recognition.

Creative Commons License

Creative Commons Attribution-Noncommercial-Share Alike 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

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Published In

Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 733-736.