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Automatic Abstracting Important Sentences

Author

Listed:
  • F. J. REN

    (Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima, Tokushima, Japan, 770-8506, Japan)

Abstract

Being increasingly popular, the Internet greatly changes our lives. We can conveniently receive and send information via the Internet. With the information explosion on the Web, it is becoming crucial to develop means to automatically extract important sentences from the Web articles. In this paper, we propose a method which uses both statistical and structural information for sentence extraction. In addition, following the analysis of human's extractions, several heuristic rules are added to filter out non-important sentences and to prevent similar sentences from being extracted. Our experimental results proved the effectiveness of these means. In particular, once the heuristic rules being added, a significant improvement has been observed.

Suggested Citation

  • F. J. Ren, 2005. "Automatic Abstracting Important Sentences," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 141-152.
    • Handle: RePEc:wsi:ijitdm:v:04:y:2005:i:01:n:s0219622005001428
    DOI: 10.1142/S0219622005001428
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    Cited by:

    1. Yiming Tang & Fuji Ren, 2016. "Variable Differently Implicational Inference for R- and S-Implications," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1235-1264, September.
    2. Yiming Tang & Fuji Ren, 2017. "Fuzzy Systems Based on Universal Triple I Method and Their Response Functions," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 443-471, March.
    3. Changqin Quan & Fuji Ren, 2016. "Visualizing Emotions from Chinese Blogs by Textual Emotion Analysis and Recognition Techniques," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 215-234, January.

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