Abstract
Plagiarism detection engines are programs that compare documents with possible sources in order to identify similarity and so discover student submissions that might be plagiarised. They are currently classified as either attribute counting systems or structure metric systems. However these classifications are Classifications of Plagiarism Detection Engines Internal Second Draft Page 1 inconsistently applied and inadequate, an area of particular relevance when classifying free text detection engines as this is where most current research is focused. This paper proposes a new and alternative set of classifications based primarily around the types of the metrics the engines use. Current detection engines are classified using the new groupings. These new classifications are intended to allow detection engines to be discussed and compared without ambiguity.
Cite
CITATION STYLE
Lancaster, T., & Culwin, F. (2005). Classifications of plagiarism detection engines. Innovation in Teaching and Learning in Information and Computer Sciences, 4(2), 1–16. https://doi.org/10.11120/ital.2005.04020006
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