Abstract

Plagiarism detection system plays an essential role in education quality improvement by helping teachers to detect plagiarism. Using a number of measures customized to determine occurrences of plagiarism is the most common approach for plagiarism detection tool. It is simple and effective, while it lacks flexibility when applied in more complicated situations. This paper proposes the MLChecker, a smart plagiarism detection system, to provide more flexible detection tactics. An automatic plagiarism dataset construction method was exploited in MLChecker to dynamically update the plagiarism detection algorithms according to different detection tasks. And the full-process quality management functions were also provided by MLChecker. The result shows that the detection accuracy is raised by 56%. Compared with traditional plagiarism detection tools, MLChecker is with higher accuracy and efficiency.

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