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We define plagiarism as: "The use of ideas, concepts, words, or structures without appropriately acknowledging the source to benefit in a setting where originality is expected." Other researchers commonly define academic plagiarism as literary theft, i.e. stealing words or ideas from other authors. Theft describes the deliberate appropriation of foreign property without the consent of the rightful owner. The definition used in this thesis does not necessarily characterize academic plagiarism as theft for the following reasons.
Plagiarism is a problem with far-reaching consequences for the sciences. However, even today’s best software-based systems can only reliably identify copy & paste plagiarism. Disguised plagiarism forms, including paraphrased text, cross-language plagiarism, as well as structural and idea plagiarism often remain undetected.
This weakness of current systems results in a large percentage of scientific plagiarism going undetected. Bela Gipp provides an overview of the state-of-the art in plagiarism detection and an analysis of why these approaches fail to detect disguised plagiarism forms. The author proposes Citation-based Plagiarism Detection to address this shortcoming.
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