IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v8y2017i1p22-39.html
   My bibliography  Save this article

Agents Oriented Genetic-K-Means (AOGK) System for Plagiarism Detection

Author

Listed:
  • Hadj Ahmed Bouarara

    (Department of Computer Science Tahar Moulay University of Saida Algeria, Saida Algeria, Algeria)

  • Yasmin Bouarara

    (Department of Computer Science, Tahar Moulay University of Saida Algeria, Saida Algeria, Algeria)

Abstract

In the last decade, the plagiarism phenomenon has widely spread and become a topical problem in the modern scientific world, caused by the wide availability of electronic documents online and offline. This work will be devoted to describe a new plagiarism detection system named AOGK « Agents Oriented Genetic-K-means » based on a multi-agents architecture composed of three modules: text parsing to transform documents into vectors; Learning module using genetic algorithms to build a prediction model; Test module using k-means for the final classification of suspicious document; To evaluate their system the authors have used a range of reference metrics (precision, recall, f-measure and entropy) and the benchmark PAN 09. They have compared the results obtained with the performance of other systems found in literature; the authors' aim is the preservation of copyright.

Suggested Citation

  • Hadj Ahmed Bouarara & Yasmin Bouarara, 2017. "Agents Oriented Genetic-K-Means (AOGK) System for Plagiarism Detection," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 8(1), pages 22-39, January.
    • Handle: RePEc:igg:joris0:v:8:y:2017:i:1:p:22-39
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJORIS.2017010102
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:joris0:v:8:y:2017:i:1:p:22-39. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.