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New Technology of Library and Information Service  2007, Vol. 2 Issue (12): 57-63    DOI: 10.11925/infotech.1003-3513.2007.12.12
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Comparative Study on HMM and CRFs Applying in Information Extraction
Wang Hao  Deng Sanhong
(Department of Information Management, Nanjing University,Nanjing 210093,China)
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This paper brings forward two models for person-name entity extraction based on the comparison of math theory between HMM and CRFs, one using word role label based HMM and the other using character role label based CRFs, then validates and compares the effect of both by open-testing and applying in practice, and thereby proves in practice that CRFs is fitter for sequence labeling and object classifying than HMM.

Key wordsHMM      CRFs      Information extraction      Person-name entity extraction      Role label      Feature     
Received: 11 October 2007      Published: 25 December 2007


Corresponding Authors: Wang Hao     E-mail:
About author:: Wang Hao,Deng Sanhong

Cite this article:

Wang Hao,Deng Sanhong. Comparative Study on HMM and CRFs Applying in Information Extraction. New Technology of Library and Information Service, 2007, 2(12): 57-63.

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