Class Meeting for 10-707 9/21/2009

This is one of the class meetings on the schedule for the course Information Extraction 10-707 in Fall 2009.

Hidden Markov models and Maxent Markov Models

• Slides

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
  • I'm going to actually present substantial parts of this in class 9/21, so I'm taking it off the "optional" list - Wcohen 21:36, 19 September 2009 (UTC)

• Mike Collins on learning in NLP, including a section on maxent taggers.
• Dan Klein on maxent.