Plagiarism Detection - State-of-the-art systems (2016) and evaluation methods

March 08, 2016 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Christina Kraus arXiv ID 1603.03014 Category cs.IR: Information Retrieval Cross-listed cs.CY, cs.DL Citations 10 Venue arXiv.org Last Checked 4 months ago
Abstract
Plagiarism detection systems comprise various approaches that aim to create a fair environment for academic publications and appropriately acknowledge the authors' works. While the need for a reliable and performant plagiarism detection system increases with an increasing amount of publications, current systems still have shortcomings. Particularly intelligent research plagiarism detection still leaves room for improvement. An important factor for progress in research is a suitable evaluation framework. In this paper, we give an overview on the evaluation of plagiarism detection. We then use a taxonomy provided in former research, to classify recent approaches of plagiarism detection. Based on this, we asses the current research situation in the field of plagiarism detection and derive further research questions and approaches to be tackled in the future.
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