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Analyzing Non-Textual Content Elements to Detect Academic Plagiarism

Norman Meuschke (Autor)

Buch | Softcover

XXIII, 272 Seiten

2023 | 1st ed. 2023
Springer Fachmedien Wiesbaden GmbH (Verlag)
978-3-658-42061-1 (ISBN)

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Identifying plagiarism is a pressing problem for research institutions, publishers, and funding bodies. Current detection methods focus on textual analysis and find copied, moderately reworded, or translated content. However, detecting more subtle forms of plagiarism, including strong paraphrasing, sense-for-sense translations, or the reuse of non-textual content and ideas, remains a challenge. This book presents a novel approach to address this problem-analyzing non-textual elements in academic documents, such as citations, images, and mathematical content. The proposed detection techniques are validated in five evaluations using confirmed plagiarism cases and exploratory searches for new instances. The results show that non-textual elements contain much semantic information, are language-independent, and resilient to typical tactics for concealing plagiarism. Incorporating non-textual content analysis complements text-based detection approaches and increases the detection effectiveness, particularly for disguised forms of plagiarism. The book introduces the first integrated plagiarism detection system that combines citation, image, math, and text similarity analysis. Its user interface features visual aids that significantly reduce the time and effort users must invest in examining content similarity.

Norman Meuschke is a Senior Researcher for Information Retrieval and Natural Language Processing at the University of Göttingen, Germany.

Introduction.- Academic Plagiarism Detection.- Citation-based Plagiarism Detection.- Image-based Plagiarism Detection.- Math-based Plagiarism Detection.- Hybrid Plagiarism Detection System.- Conclusion and Future Work.- References.

Erscheinungsdatum	02.08.2023
Zusatzinfo	XXIII, 272 p. 55 illus. Textbook for German language market.
Verlagsort	Wiesbaden
Sprache	englisch
Maße	148 x 210 mm
Gewicht	389 g
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Schlagworte	Citation analysis • content-based image retrieval • Information Visualization • Math Retrieval • Natural Language Processing • plagiarism detection
ISBN-10	3-658-42061-8 / 3658420618
ISBN-13	978-3-658-42061-1 / 9783658420611
Zustand	Neuware