TEIMMA: The First Content Reuse Annotator for Text, Images, and Math
Ankit Satpute, André Greiner-Petter, Moritz Schubotz, Norman Meuschke, Akiko Aizawa, Olaf Teschke, Bela Gipp
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- github.com/gipplab/teimma-reuse-annotatorOfficialIn paperpytorch★ 0
Abstract
This demo paper presents the first tool to annotate the reuse of text, images, and mathematical formulae in a document pair -- TEIMMA. Annotating content reuse is particularly useful to develop plagiarism detection algorithms. Real-world content reuse is often obfuscated, which makes it challenging to identify such cases. TEIMMA allows entering the obfuscation type to enable novel classifications for confirmed cases of plagiarism. It enables recording different reuse types for text, images, and mathematical formulae in HTML and supports users by visualizing the content reuse in a document pair using similarity detection methods for text and math.