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Multi-document Summarization Based on Link Analysis and Text Classification

  • Conference paper
Digital Libraries: International Collaboration and Cross-Fertilization (ICADL 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3334))

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Abstract

This paper describes a multi-document summarizer in Chinese, ACRUX, which contains three new techniques: a fuzzy classification method based on KNN (FAMKNN), Subject-Oriented Multi-document Summarization (SOMS), and Multi-document Summarization with Link Analysis.

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Author information

Authors and Affiliations

  1. The Institute of Artificial Intelligence, Zhejiang University, Hangzhou, 310027, P.R. China

    Jiangqin Wu, Yizi Wu, Jian Liu & Yueting Zhuang

Authors
  1. Jiangqin Wu
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  2. Yizi Wu
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  3. Jian Liu
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  4. Yueting Zhuang
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Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, P.R. China

    Zhaoneng Chen

  2. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  3. Shanghai Library, Shanghai, P.R. China

    Qihao Miao

  4. BASICS, Department of Computer Science and Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China

    Yuxi Fu

  5. Digital Library Research Laboratory, Virginia Tech, USA

    Edward Fox

  6. School of Computer Engineering, Nanyang Technological University,  

    Ee-peng Lim

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© 2004 Springer-Verlag Berlin Heidelberg

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Cite this paper

Wu, J., Wu, Y., Liu, J., Zhuang, Y. (2004). Multi-document Summarization Based on Link Analysis and Text Classification. In: Chen, Z., Chen, H., Miao, Q., Fu, Y., Fox, E., Lim, Ep. (eds) Digital Libraries: International Collaboration and Cross-Fertilization. ICADL 2004. Lecture Notes in Computer Science, vol 3334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30544-6_82

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  • DOI: https://doi.org/10.1007/978-3-540-30544-6_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24030-3

  • Online ISBN: 978-3-540-30544-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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