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An Enhanced Plagiarism Detection Based on Syntactico-Semantic Knowledge

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Intelligent Systems Design and Applications (ISDA 2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 941))

Abstract

The issue of plagiarism in documents has been present for centuries. Yet, the widespread dissemination of information technology, including the internet, made plagiarism much easier. Consequently, methods and systems aiding in the detection of plagiarism have attracted much research within the last two decades. This paper introduces a plagiarism detection technique based on the semantic knowledge, notably semantic class and thematic role. This technique analyzes and compares text based on the semantic allocation for each term in the sentence. Semantic knowledge is superior in semantically generating arguments for each sentence. Weighting for each argument generated by semantic knowledge to study its behavior is also introduced in this paper. It was found that not all arguments affect the plagiarism detection process.

In addition, experimental results on PAN13-14 (http://pan.webis.de/.) data sets revealed significant speed-up, which outperforms the recent methods for plagiarism detection in terms of Recall and Precision measure.

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Authors and Affiliations

  1. MIRACL Laboratory, Sfax University, Sfax, Tunisia

    Wafa Wali, Bilel Gargouri & Abdelmajid Ben Hamadou

Authors
  1. Wafa Wali
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  2. Bilel Gargouri
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  3. Abdelmajid Ben Hamadou
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Corresponding authors

Correspondence to Wafa Wali , Bilel Gargouri or Abdelmajid Ben Hamadou .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, WA, USA

    Ajith Abraham

  2. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Aswani Kumar Cherukuri

  3. Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Melin

  4. Machine Intelligence Research Labs, Auburn, WA, USA

    Niketa Gandhi

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Wali, W., Gargouri, B., Ben Hamadou, A. (2020). An Enhanced Plagiarism Detection Based on Syntactico-Semantic Knowledge. In: Abraham, A., Cherukuri, A., Melin, P., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2018 2018. Advances in Intelligent Systems and Computing, vol 941. Springer, Cham. https://doi.org/10.1007/978-3-030-16660-1_26

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