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International Conference on Neural Information Processing

ICONIP 2009: Neural Information Processing pp 216–225Cite as

Swarm Diversity Based Text Summarization

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5864))

Abstract

Automatic text summarization systems aim to make their created summaries closer to human summaries. The summary creation under the condition of the redundancy and the summary length limitation is a challenge problem. The automatic text summarization system which is built based on exploiting of the advantages of different techniques in form of an integrated model could produce a good summary for the original document. In this paper, we introduced an integrated model for automatic text summarization problem; we tried to exploit different techniques advantages in building of our model like advantage of diversity based method which can filter the similar sentences and select the most diverse ones and advantage of the differentiation between the most important features and less important using swarm based method. The experimental results showed that our model got the best performance over all methods used in this study.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

    Mohammed Salem Binwahlan & Naomie Salim

  2. Faculty of Science and Technology, Suan Dusit Rajabhat University, 295 Ratchasrima Rd, Dusit, Bangkok, Thailand, 10300

    Ladda Suanmali

Authors
  1. Mohammed Salem Binwahlan
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  2. Naomie Salim
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  3. Ladda Suanmali
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, City University of Hong Kong, Hong Kong,  

    Chi Sing Leung

  2. School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  3. School of Information Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-U-Thit Rd., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Jonathan H. Chan

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© 2009 Springer-Verlag Berlin Heidelberg

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Binwahlan, M.S., Salim, N., Suanmali, L. (2009). Swarm Diversity Based Text Summarization. In: Leung, C.S., Lee, M., Chan, J.H. (eds) Neural Information Processing. ICONIP 2009. Lecture Notes in Computer Science, vol 5864. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10684-2_24

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  • DOI: https://doi.org/10.1007/978-3-642-10684-2_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10682-8

  • Online ISBN: 978-3-642-10684-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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