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Rhetorical Figuration as a Metric in Text Summarization

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Advances in Artificial Intelligence (Canadian AI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8436))

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Abstract

We show that surface-level markers of pragmatic intent can be used to recognize the important sentences in text and can thereby improve the performance of text summarization systems. In particular, we focus on using automated detection of rhetorical figures—characteristic syntactic patterns of persuasive language—to provide information for an additional metric to enhance the performance of the MEAD summarizer.

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Authors and Affiliations

  1. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

    Mohammed Alliheedi & Chrysanne Di Marco

Authors
  1. Mohammed Alliheedi
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  2. Chrysanne Di Marco
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Editor information

Editors and Affiliations

  1. Faculty of Medicine and School of Electrical Engineering and Computer Science, Department of Epidemiology & Community Medicine, University of Ottawa, 451 Smyth Road, Room 3105, K1H 8M5, Ottawa, ON, Canada

    Marina Sokolova

  2. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    Peter van Beek

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Alliheedi, M., Di Marco, C. (2014). Rhetorical Figuration as a Metric in Text Summarization. In: Sokolova, M., van Beek, P. (eds) Advances in Artificial Intelligence. Canadian AI 2014. Lecture Notes in Computer Science(), vol 8436. Springer, Cham. https://doi.org/10.1007/978-3-319-06483-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-06483-3_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06482-6

  • Online ISBN: 978-3-319-06483-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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