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Survey on Plagiarism Detection Systems and Their Comparison

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Computational Intelligence in Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 990))

Abstract

Plagiarism occurs when a person uses someone’s work, ideas, words, expressions without giving the required attribution. Plagiarism is a common problem in fields like academia, Research papers, Publications, Patents, etc. In this paper, we deliberate the techniques for detecting the extrinsic plagiarism. These techniques are based on linguistic features, Semantic role labelling, vector space model, Fuzzy semantic string matching, and N-gram approach. And are tested on PAN plagiarism corpus 2009 and PAN plagiarism corpus 2011.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, UIET, Panjab University, Chandigarh, 160014, India

    Lovepreet, Vishal Gupta & Rohit Kumar

Authors
  1. Lovepreet
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  2. Vishal Gupta
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  3. Rohit Kumar
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Corresponding authors

Correspondence to Lovepreet or Vishal Gupta .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Faculty of Communication Sciences, University of Teramo, Teramo, Italy

    Danilo Pelusi

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Lovepreet, Gupta, V., Kumar, R. (2020). Survey on Plagiarism Detection Systems and Their Comparison. In: Behera, H., Nayak, J., Naik, B., Pelusi, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 990. Springer, Singapore. https://doi.org/10.1007/978-981-13-8676-3_3

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