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Using another feature selection algorithm for POS Tagging based on Maximum Entropy Principle
Yao Ning * #
Center for Intelligence Science and Technology Research,Beijing University of Posts and Telecommunications
*Correspondence author
#Submitted by
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Funding: none
Opened online: 9 November 2007
Accepted by: none
Citation: Yao Ning.Using another feature selection algorithm for POS Tagging based on Maximum Entropy Principle[OL]. [ 9 November 2007] http://en.paper.edu.cn/en_releasepaper/content/16257
 
 
Maximum Entropy model is widely used in natural language processing in many fields, this paper uses Maximum Entropy model to build a part-of-speech tagging system based on the special needs. Because of the huge difference of grammar and structure between Chinese and English, this paper focuses on feature selection’s influence on the premise that its feature template is selected. And we use a feature selection algorithm-iteration, modification, and cutting (IMC) applied to Maximum Entropy model. The experiment shows that we can gain a better result through appropriate feature selection methods.
Keywords:Maximum Entropy feature selection feature template IMC
 
 
 

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