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Scaling conditional random fields for na... - PDF Document (1 M) |
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| Access Rights |
Open Access |
| Citation |
Cohn, T. A. (2007). Scaling conditional random fields for natural language processing , PhD thesis, Department of Computer Science and Software Engineering, University of Melbourne. |
| Handle |
10187/1948 |
| Title |
Scaling conditional random fields for natural language processing |
| Creator |
Cohn, Trevor A |
| Date |
2007-01 |
| Subject / Keywords |
conditional random fields, natural language processing, graphical models, maximum entropy |
| Abstract |
This thesis deals with the use of Conditional Random Fields (CRFs; Lafferty et al. (2001)) for Natural Language Processing (NLP). CRFs are probabilistic models for sequence labelling which are particularly well suited to NLP. They have many compelling advantages over other popular models such as Hidden Markov Models and Maximum Entropy Markov Models (Rabiner, 1990; McCallum et al., 2001), and have been applied to a number of NLP tasks with considerable success (e.g., Sha and Pereira (2003) and Smith et al. (2005)). Despite their apparent success, CRFs suffer from two main failings. Firstly, they often over-fit the training sample. This is a consequence of their considerable expressive power, and can be limited by a prior over the model parameters (Sha and Pereira, 2003; Peng and McCallum, 2004). Their second failing is that the standard methods for CRF training are often very slow, sometimes requiring weeks of processing time. This efficiency problem is largely ignored in current literature, although in practise the cost of training prevents the application of CRFs to many new more complex tasks, and also prevents the use of densely connected graphs, which would allow for much richer feature sets. (For complete abstract open document) |
| Type |
PhD thesis |
| Language |
eng |
| Notes |
© 2007 Dr. Trevor A. Cohn |
| Publication Status |
Inpress |
| Peer Reviewed |
Peer Reviewed |
| Faculty/Department |
Engineering: Department of Computer Science and Software Engineering |
| Faculty/Department |
Department of Computer Science and Software Engineering |
| Institution |
University of Melbourne |
| Collection |
Research Collections (UMER) |
| Rights |
Terms and Conditions: Copyright in works deposited in the University of Melbourne Eprints Repository (UMER) is retained by the copyright owner. The work may not be altered without permission from the copyright owner. Readers may only, download, print, and save electronic copies of whole works for their own personal non-commercial use. Any use that exceeds these limits requires permission from the copyright owner. Attribution is essential when quoting or paraphrasing from these works. |
| PID |
67119 |
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