To mitigate the risk of subjectivity concerning the selection and presentation of content, we adhered to best practice guidelines for conducting systematic reviews and investigated the taxonomies and structure set forward in related reviews. We present the insights in the latter investigation during the following section.

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To answer these questions, we Arrange the rest of this article as follows. The section Methodology

If your classification accuracy drops significantly, then the suspicious and known documents are likely from the same author; otherwise, they are likely written by different authors [232]. There is no consensus over the stylometric features that are most suitable for authorship identification [158]. Table 21 gives an overview of intrinsic detection methods that make use of machine-learning techniques.

Our review will be the first that adheres for the guidelines for conducting systematic literature surveys.

synthesizes the classifications of plagiarism found from the literature into a technically oriented typology suitable for our review. The section Plagiarism Detection Methods

VSM keep on being popular and properly-performing strategies not only for detecting copy-and-paste plagiarism but will also for identifying obfuscated plagiarism as part of a semantic analysis.

Hourrane and Benlahmar [114] described specific research papers in detail but didn't offer an abstraction of the presented detection methods.

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, summarizes the contributions of our compared to topically related reviews published considering the fact that 2013. The section Overview from the Research Field

Most on the algorithms for style breach detection follow a three-step process [214]: Text segmentation

Properties of small technical importance are: how much from the content represents possible plagiarism;

Getting made these rewrite plagiarism free tool generator minecraft account adjustments to our search strategy, we started the third phase in the data collection. We queried Google Scholar with the following keywords related to specific sub-topics of plagiarism detection, which we experienced determined as important during the first and second phases: semantic analysis plagiarism detection, machine-learning plagiarism detection

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