An academic Arabic corpus for plagiarism detection: design, construction and experimentation

Author:

Al-Thwaib Eman,Hammo Bassam H.ORCID,Yagi Sane

Abstract

AbstractAdvancement in information technology has resulted in massive textual material that is open to appropriation. Due to researchers’ misconduct, a plethora of plagiarism detection (PD) systems have been developed. However, most PD systems on the market do not support the Arabic language. In this paper, we discuss the design and construction of an Arabic PD reference corpus that is dedicated to academic language. It consists of (2312) dissertations that were defended by postgraduate students at the University of Jordan (JU) between the years 2001–2016. This Academic Jordan University Plagiarism Detection corpus; henceforth, JUPlag, follows the Dewey decimal classification (DDC) in the way it is structured. The goal of the corpus is twofold: Firstly, it is a database for the detection of plagiarism in student assignments, reports, and dissertations. Secondly, the n-gram structure of the corpus provides a knowledgebase for linguistic analysis, language teaching, and the learning of plagiarism-free writing. The PD system is guided by JU Library’s metadata for retrieval and discovery of plagiarism. To test JUPlag, we injected an unseen dissertation with multiple instances of plagiarism-simulated paragraphs and sentences. Experimentation with the system using different verbatim n-gram segments is indeed promising. Preliminary results encourage that permission be sought to enrich this corpus with all the theses in the Thesis Repository of the Union of Arab Universities. The JUPlag corpus is intended to function as an indispensable source for testing and evaluating plagiarism detection techniques. Since the University of Jordan is seeking to become a center for plagiarism detection for Arabic content and being a non-profit organization, it will charge a nominal fee for the use of JUPlag to finance the maintenance and development of the corpus.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Education

Reference52 articles.

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4. Bensalem, I., Boukhalfa, I., Rosso, P., Abouenour, L., Darwish, K., & Chikhi, S. (2015). Overview of the AraPlagDet PAN@ FIRE2015 shared task on Arabic plagiarism detection. In FIRE workshops, (pp. 111–122).

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