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Graph-Based Query-Focused Multi-document Summarization Using Improved Affinity Graph

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Book cover Knowledge Science, Engineering and Management (KSEM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9403))

Abstract

Manifold ranking is one of the most competitive approaches for query-focused multi-document summarization. Despite its success for this task, it usually constructs a sentence affinity graph first based on inter-sentence content similarity, and then perform manifold ranking on the graph to score each sentence with the assumption that all the sentences live on a single manifold. Actually, for a document set to be summarized, the distribution of the sentences might form different, but related manifolds. This paper aims to generalize the basic manifold-ranking based approach to the more generic setting by introducing a novel affinity graph to estimate the similarity between sentences, which leverages both the local geometric structures and the contents of sentences jointly. Preliminary experimental results on the DUC datasets demonstrate the good effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. School of Computer Science, Central China Normal University, Wuhan, China

    Po Hu & Yong Zhang

  2. Medallia Inc., Palo Alto, USA

    Jiacong He

Authors
  1. Po Hu
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  2. Jiacong He
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  3. Yong Zhang
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Corresponding author

Correspondence to Po Hu .

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Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Songmao Zhang

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Martin Wirsing

  3. Southwest University, Chongqing, China

    Zili Zhang

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Hu, P., He, J., Zhang, Y. (2015). Graph-Based Query-Focused Multi-document Summarization Using Improved Affinity Graph. In: Zhang, S., Wirsing, M., Zhang, Z. (eds) Knowledge Science, Engineering and Management. KSEM 2015. Lecture Notes in Computer Science(), vol 9403. Springer, Cham. https://doi.org/10.1007/978-3-319-25159-2_31

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  • DOI: https://doi.org/10.1007/978-3-319-25159-2_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25158-5

  • Online ISBN: 978-3-319-25159-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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