Combining mathematical content similarity, citation analysis, and text similarity in a two-stage process improves detection of concealed academic plagiarism in STEM documents, as evaluated on confirmed cases and applied to 102K documents.
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Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathematical Content and Citations
Combining mathematical content similarity, citation analysis, and text similarity in a two-stage process improves detection of concealed academic plagiarism in STEM documents, as evaluated on confirmed cases and applied to 102K documents.