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AntiPlag: plagiarism detection on electronic submissions of text-based assignments

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dc.contributor.author Jiffriya, M. A. C.
dc.contributor.author Akmal Jahan, M. A. C.
dc.contributor.author Roshan, G. Ragel
dc.contributor.author Sampath, Deegalla
dc.date.accessioned 2022-09-28T10:33:28Z
dc.date.available 2022-09-28T10:33:28Z
dc.date.issued 2014-03
dc.identifier.citation 08th International Conference on Industrial and Information Systems (ICIIS) on 17-20 December 2013, University of Peradeniya, Peradeniya. pp. 1-5. en_US
dc.identifier.isbn 978-1-4799-0908-7
dc.identifier.issn 2164-7011
dc.identifier.uri https://www.researchgate.net/publication/260604317
dc.identifier.uri http://ir.lib.seu.ac.lk/handle/123456789/6257
dc.description.abstract Plagiarism is one of the growing issues in academia and is always a concern in Universities and other academic institutions. The situation is becoming even worse with the availability of ample resources on the web. This paper focuses on creating an effective and fast tool for plagiarism detection for text-based electronic assignments. Our plagiarism detection tool named AntiPlag is developed using the tri-gram sequence matching technique. Three sets of text-based assignments were tested by AntiPlag and the results were compared against an existing commercial plagiarism detection tool. AntiPlag showed better results in terms of false positives compared to the commercial tool due to the pre-processing steps performed in AntiPlag. In addition, to improve the detection latency, AntiPlag applies a data clustering technique making it four times faster than the commercial tool considered. AntiPlag could be used to isolate plagiarized text-based assignments from non-plagiarised assignments easily. Therefore, we present AntiPlag, a fast and effective tool for plagiarism detection on text based electronic assignments. en_US
dc.language.iso en_US en_US
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) en_US
dc.subject Terms-Plagiarism Detection en_US
dc.subject AntiPlag en_US
dc.subject Electronic Assignments en_US
dc.title AntiPlag: plagiarism detection on electronic submissions of text-based assignments en_US
dc.type Article en_US


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  • Research Articles [915]
    THESE ARE RESEARCH ARTICLES OF ACADEMIC STAFF, PUBLISHED IN JOURNALS AND PROCEEDINGS ELSWHERE

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