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Experimental Study of Chinese Free-Text IE Algorithm Based on WCA-Selection Using Hidden Markov Model

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Information Retrieval Technology (AIRS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4993))

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Abstract

This paper proposes the extraction task of the Chinese Sci-tech journal text and presents a WCA-Selection Chinese free-text HMM IE algorithm. The HMM IE algorithm takes the Chinese Sci-tech journal abstract text as the extraction text. According to the features of WCA, an idea of WCA selection model re-optimization is proposed. And a WCA selection optimization strategy is concreted. Then the experimental verification is conducted with a satisfied result. The experiment results show that the designed extraction algorithm and WCA selection optimization strategy have good performance in the the Chinese Sci-tech journal abstract text.

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Author information

Authors and Affiliations

  1. Optical Memory National Engineering Research Center, State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, 100084, China

    Qian Liu, Hui Jiao & Hui-bo Jia

Authors
  1. Qian Liu
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  2. Hui Jiao
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  3. Hui-bo Jia
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Editor information

Hang Li Ting Liu Wei-Ying Ma Tetsuya Sakai Kam-Fai Wong Guodong Zhou

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© 2008 Springer-Verlag Berlin Heidelberg

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Liu, Q., Jiao, H., Jia, Hb. (2008). Experimental Study of Chinese Free-Text IE Algorithm Based on WCA-Selection Using Hidden Markov Model. In: Li, H., Liu, T., Ma, WY., Sakai, T., Wong, KF., Zhou, G. (eds) Information Retrieval Technology. AIRS 2008. Lecture Notes in Computer Science, vol 4993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68636-1_78

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  • DOI: https://doi.org/10.1007/978-3-540-68636-1_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68633-0

  • Online ISBN: 978-3-540-68636-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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