Information Extraction from Chinese Papers Based on Hidden Markov Model

Cheng Ying Chi; Yan Zhang

doi:10.4028/www.scientific.net/AMR.846-847.1291

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 846-847Information Extraction from Chinese Papers Based...

Information Extraction from Chinese Papers Based on Hidden Markov Model

Abstract:

Hidden Markov model HMM (1) is one of the important approaches for information extraction. In this paper, a model of the improved first-order hidden Markov HMM (2) is proposed. In the HMM (2), the output probability of the observation is not only dependent on the current state of the model, but also dependent on the previous state of the current state of the model. The algorithm of the ML and the algorithm of the Viterbi are analyzed. At last, experiments show that the HMM (2) is more precise than the HMM (1).

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Periodical:

Advanced Materials Research (Volumes 846-847)

Pages:

1291-1294

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.846-847.1291

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Cite this paper

Online since:

November 2013

Authors:

Cheng Ying Chi*, Yan Zhang

Keywords:

Improved First-Order Hidden Markov Model, Information Extraction, Precision, Traditional First-Order Hidden Markov Model

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* - Corresponding Author

References

[1] Zhang Ling, Huang Tiejun, Gao Wen. Citation information extraction based on Hidden Markov model[J]. Computer Engineering, 2003, 29(20) 33-34.

Google Scholar

[2] Zhao Hui, Gu Yaqiang, Tang Chaojing. Bimodal Speech Recognition Approach Based on Product HMM[J]. Computer Engineering, 2010, 63(8) 7-9.

Google Scholar

[3] Liu Yunzhong, Lin Yaping, Chen Zhiping. Text Information Extraction Based on Hidden Markov Model[J]. Journal of System Simulation , 2004, 16(3) 507-510.

DOI: 10.1109/nlpke.2003.1275937

Google Scholar

[4] Zhu Weihu, Lu Yi, Liu Binbin. Improvement of Web Information Extraction Algorithm Bsaed on HMM[J]. Computer Science, 2010, 37(2) 203-206.

Google Scholar

[5] Freitag D, McCallum A. Information Extraction with HMM Structures Learned by Stochastic Optimization Proceedings of the 18th Conference on Artificial Intelligence[J]. 2000 584-589.

Google Scholar