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Article Information:
Application of EM Algorithm in Statistics Natural Language Processing
Xuexia Gao and Yun Wang
Corresponding Author: Xuexia Gao
Submitted: September 16, 2012
Accepted: October 31, 2012
Published: March 25, 2013 |
Abstract:
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This study describes the basic framework of EM algorithm and gives how to apply EM algorithm to solve the problem of maximum-likelihood parameters estimation combining with the models of HMM and PCFG. In the process of statistics natural language, one kind of problem is often encountered that is how to solve the parameter's maximum-likelihood estimation when observation data is incomplete. EM algorithm is the classical method to solve this problem. Finally, the advantages and disadvantages of EM algorithm are discussed.
Key words: Context-free grammar, EM algorithm, hidden Markov model, likelihood function, natural language, parameter estimation ,
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Cite this Reference:
Xuexia Gao and Yun Wang, . Application of EM Algorithm in Statistics Natural Language Processing. Research Journal of Applied Sciences, Engineering and Technology, (10): 2969-2973.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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