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Filtering Documents for Plagiarism Detection

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Discovery Science (DS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11198))

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Abstract

Efficient methods are required for plagiarism detection. This paper proposes a fast and scalable method for detecting “copy and paste”-type plagiarism in documents. Implementing detection methods for this type of plagiarism requires a long processing time or a large database for comprehensive matching of ordered word occurrences. The author improved the scalability of an existing fast method based on fast Fourier transform using the idea of the frequency domain filtering. He evaluated the effect of the improvement on accuracy of the plagiarism detection method, and achieved an effective trade-off between the accuracy and the required size of database.

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Author information

Authors and Affiliations

  1. Fujitsu Laboratories, Kawasaki, 211-8581, Japan

    Kensuke Baba

Authors
  1. Kensuke Baba
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Correspondence to Kensuke Baba .

Editor information

Editors and Affiliations

  1. Goldsmiths University of London, London, UK

    Larisa Soldatova

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Joaquin Vanschoren

  3. University of Cyprus, Nicosia, Cyprus

    George Papadopoulos

  4. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

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Baba, K. (2018). Filtering Documents for Plagiarism Detection. In: Soldatova, L., Vanschoren, J., Papadopoulos, G., Ceci, M. (eds) Discovery Science. DS 2018. Lecture Notes in Computer Science(), vol 11198. Springer, Cham. https://doi.org/10.1007/978-3-030-01771-2_23

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  • DOI: https://doi.org/10.1007/978-3-030-01771-2_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01770-5

  • Online ISBN: 978-3-030-01771-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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