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An Innovative Similarity Measure for Sentence Plagiarism Detection

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Computational Science and Its Applications – ICCSA 2016 (ICCSA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9790))

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Abstract

We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.

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Author information

Authors and Affiliations

  1. Istituto di Calcolo E Reti Ad Alte Prestazioni (ICAR), Italian National Research Council (CNR), Palermo, Italy

    Agnese Augello, Alfredo Cuzzocrea, Giovanni Pilato & Carmelo Spiccia

  2. University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea

  3. Universitá degli Studi di Palermo, Palermo, Italy

    Giorgio Vassallo

Authors
  1. Agnese Augello
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  2. Alfredo Cuzzocrea
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  3. Giovanni Pilato
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  4. Carmelo Spiccia
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  5. Giorgio Vassallo
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Corresponding author

Correspondence to Alfredo Cuzzocrea .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  5. Polytechnic University, Bari, Italy

    Carmelo M. Torre

  6. Monash University, Clayton, Victoria, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  9. Beijing University of Posts and Telecommunications, Beijing, China

    Shangguang Wang

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Augello, A., Cuzzocrea, A., Pilato, G., Spiccia, C., Vassallo, G. (2016). An Innovative Similarity Measure for Sentence Plagiarism Detection. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9790. Springer, Cham. https://doi.org/10.1007/978-3-319-42092-9_42

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  • DOI: https://doi.org/10.1007/978-3-319-42092-9_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42091-2

  • Online ISBN: 978-3-319-42092-9

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