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An Adaptive Image-based Plagiarism Detection Approach
2018
Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries - JCDL '18
Identifying plagiarized content is a crucial task for educational and research institutions, funding agencies, and academic publishers. Plagiarism detection systems available for productive use reliably identify copied text, or near-copies of text, but often fail to detect disguised forms of academic plagiarism, such as paraphrases, translations, and idea plagiarism. To improve the detection capabilities for disguised forms of academic plagiarism, we analyze the images in academic documents as
doi:10.1145/3197026.3197042
dblp:conf/jcdl/MeuschkeGSBKG18
fatcat:uesb4oemsjdrre5kyn7q5sle6u