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

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

Hadj Ahmed Bouarara, Yasmin Bouarara
Copyright: © 2017 |Volume: 8 |Issue: 1 |Pages: 18
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781522513292|DOI: 10.4018/IJORIS.2017010102
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MLA

Bouarara, Hadj Ahmed, and Yasmin Bouarara. "Agents Oriented Genetic-K-Means (AOGK) System for Plagiarism Detection." IJORIS vol.8, no.1 2017: pp.22-39. http://doi.org/10.4018/IJORIS.2017010102

APA

Bouarara, H. A. & Bouarara, Y. (2017). Agents Oriented Genetic-K-Means (AOGK) System for Plagiarism Detection. International Journal of Operations Research and Information Systems (IJORIS), 8(1), 22-39. http://doi.org/10.4018/IJORIS.2017010102

Chicago

Bouarara, Hadj Ahmed, and Yasmin Bouarara. "Agents Oriented Genetic-K-Means (AOGK) System for Plagiarism Detection," International Journal of Operations Research and Information Systems (IJORIS) 8, no.1: 22-39. http://doi.org/10.4018/IJORIS.2017010102

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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.

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