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Graph-Based Multi-Document Summarization: An Initial Investigation

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Research and Development in Intelligent Systems XXXII (SGAI 2015)

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Abstract

With the explosion of information on the Internet, manual summarization has become an unrealistic solution, and the need for automatic summarization–more specifically, multi-document summarization–has grown. Automatic summarization provides the most significant and relevant information while saving time and effort. This paper proposes a graph-based multi-document summarization model to produce extractive multi-document summaries. The model formulates the summarization problem as a capacitated profitable tour problem to optimize the coverage and coherence of the resulting summary. The solution is approximated using swarm intelligence meta-heuristics.

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Notes

  1. 1.

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Author information

Authors and Affiliations

  1. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

    Asma Bader Al-Saleh

  2. Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh, 11543, Saudi Arabia

    Mohamed El Bachir Menai

Authors
  1. Asma Bader Al-Saleh
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  2. Mohamed El Bachir Menai
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Corresponding author

Correspondence to Asma Bader Al-Saleh .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, United Kingdom

    Max Bramer

  2. School of Computing, Engineering and Mathematics, University of Brighton, Brighton, United Kingdom

    Miltos Petridis

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Al-Saleh, A.B., Menai, M.E.B. (2015). Graph-Based Multi-Document Summarization: An Initial Investigation. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXXII. SGAI 2015. Springer, Cham. https://doi.org/10.1007/978-3-319-25032-8_13

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  • DOI: https://doi.org/10.1007/978-3-319-25032-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25030-4

  • Online ISBN: 978-3-319-25032-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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