Abstract
In recent years, several methods and tools been developed together with test collections to aid in plagiarism detection. However, both methods and collections have focused on content analysis, overlooking citation analysis. In this paper, we aim at filling this gap and present a test collection with cases of plagiarism by missing and incorrect references. The collection contains automatically generated academic papers in which passages from other documents have been inserted. Such passages were either: adequately referenced (i.e., not plagiarized), not referenced, or incorrectly referenced. Annotation files identifying each passage enable the evaluation of plagiarism detection systems. © 2012 Springer-Verlag.
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CITATION STYLE
De L. Pertile, S., & Moreira, V. P. (2012). A test collection to evaluate plagiarism by missing or incorrect references. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7488 LNCS, pp. 141–143). https://doi.org/10.1007/978-3-642-33247-0_17
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