Hybrid plagiarism detection method for French language

Article type: Research Article

Authors: Elamine, Maryam^* | Mechti, Seifeddine | Belguith, Lamia Hadrich

Affiliations: University of Sfax, Sfax, Tunisia

Correspondence: [*] Corresponding author: Maryam Elamine, ANLP-RG, MIRACL laboratory, University of Sfax, Sfax, Tunisia. E-mail: [email protected].

Abstract: With the growth of the content found throughout the Web, every information can be plagiarized. Plagiarism is the process of using the ideas of another without naming the source. Consequently, plagiarism detection is necessary but complicated as it is often facing significant challenges given the large amount of material on the World-wide-web and the limited access to a substantial part of them. In this paper, we present a novel plagiarism detection method for French documents. The proposed method combines the intrinsic and extrinsic aspects for plagiarism detection. We achieved good results with both approaches. For the extrinsic method, we achieved an accuracy of 62% for the first tests of the method. As for the intrinsic, we achieved an F-score of 0.328.

Keywords: Intrinsic plagiarism detection, extrinsic plagiarism detection, embeddings, style-breach

DOI: 10.3233/HIS-200284

Journal: International Journal of Hybrid Intelligent Systems, vol. 16, no. 3, pp. 163-175, 2020