Outlier-Based Approaches for Intrinsic and External Plagiarism Detection

  • Gabriel Oberreuter
  • Gaston L’Huillier
  • Sebastián A. Ríos
  • Juan D. Velásquez
Conference paper

DOI: 10.1007/978-3-642-23863-5_2

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6882)
Cite this paper as:
Oberreuter G., L’Huillier G., Ríos S.A., Velásquez J.D. (2011) Outlier-Based Approaches for Intrinsic and External Plagiarism Detection. In: König A., Dengel A., Hinkelmann K., Kise K., Howlett R.J., Jain L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science, vol 6882. Springer, Berlin, Heidelberg

Abstract

Plagiarism detection, one of the main problems that educational institutions have been dealing with since the massification of Internet, can be considered as a classification problem using both self-based information and text processing algorithms whose computational complexity is intractable without using space search reduction algorithms. First, self-based information algorithms treat plagiarism detection as an outlier detection problem for which the classifier must decide plagiarism using only the text in a given document. Then, external plagiarism detection uses text matching algorithms where it is fundamental to reduce the matching space with text search space reduction techniques, which can be represented as another outlier detection problem. The main contribution of this work is the inclusion of text outlier detection methodologies to enhance both intrinsic and external plagiarism detection. Results shows that our approach is highly competitive with respect to the leading research teams in plagiarism detection.

Keywords

Text Classification Outlier Detection Search Space Reduction External Plagiarism Detection Intrinsic Plagiarism Detection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Gabriel Oberreuter
    • 1
  • Gaston L’Huillier
    • 1
  • Sebastián A. Ríos
    • 1
  • Juan D. Velásquez
    • 1
  1. 1.Web Intelligence Consortium Chile Research Centre Department of Industrial EngineeringUniversity of ChileChile

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