Difference between revisions of "Class Meeting for 10-710 09-01-2011"
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This is one of the class meetings on the [[Syllabus for Structured Prediction 10-710 in Fall 2011|schedule]] for the course [[Structured Prediction 10-710 in Fall 2011]]. | This is one of the class meetings on the [[Syllabus for Structured Prediction 10-710 in Fall 2011|schedule]] for the course [[Structured Prediction 10-710 in Fall 2011]]. | ||
| − | === Hidden | + | === Hidden Markov Models as Structured Prediction === |
* [http://www.cs.cmu.edu/~wcohen/10-707/09-20-mene+hmms.ppt Slides] | * [http://www.cs.cmu.edu/~wcohen/10-707/09-20-mene+hmms.ppt Slides] | ||
Revision as of 14:29, 19 July 2011
This is one of the class meetings on the schedule for the course Structured Prediction 10-710 in Fall 2011.
Contents
Hidden Markov Models as Structured Prediction
Required Readings
- Borkar 2001 Automatic Segmentation of Text Into Structured Records
- Frietag 2000 Maximum Entropy Markov Models for Information Extraction and Segmentation
Optional Readings
- An Algorithm that Learns What's in a Name, Bikel et al, MLJ 1999. Another well-engineered and influential HMM-based NER system.
- Unsupervised Learning of Field Segmentation Models for Information Extraction, Grenager, Klein, and Manning, ACL 2005. Unsupervised segmentation paper.
- Named Entity Recognition with Character-Level Models, Klein et al, CoNLL 2003. Interesting twist on the standard approach of token-tagging - NER by tagging characters and character n-grams.
Background Readings
- A Maximum Entropy Part-Of-Speech Tagger, Ratnaparkhi, Workshop on Very Large Corpora 1996
- Mike Collins on learning in NLP, including a section on maxent taggers.
- Dan Klein on maxent.
