Abstract
This thesis improves the capabilities to detect disguised plagiarism in academic documents, which is an open research challenge in Information Retrieval and a pressing day-to-day problem, e.g., for publishers, research institutions, and funding organizations. Section 1.1 describes the problems arising from academic plagiarism. Section 1.2 summarizes the research gap that exists regarding the detection of disguised plagiarism forms. Section 1.3 presents the research objective and research tasks that guided my doctoral research.
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Notes
- 1.
In 80 of the 207 cases, the responsible universities rescinded the academic degree, or the author returned the degree after the unoriginal content was found. In 37 cases, the universities did not rescind the degree but often issued reprimands or other sanctions. In 90 cases, official investigations are either pending or the universities did not publish the results of their investigations [538].
- 2.
In 426 of the 652 cases, the responsible institutions rescinded the academic degree, in 168 cases the institutions did not rescind the degree, and in 58 cases investigations are pending [580].
- 3.
http://portal.core.edu.au/conf-ranks, Ranks: A*—flagship conference, A—excellent conference, B—good conference, C—other ranked conferences.
- 4.
https://www.scimagojr.com, Ranks: quartiles (Q1–Q4) of the SJR scores of journals in the field.
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Meuschke, N. (2023). Introduction. In: Analyzing Non-Textual Content Elements to Detect Academic Plagiarism. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-42062-8_1
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DOI: https://doi.org/10.1007/978-3-658-42062-8_1
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