Abstract
Plagiarism is a problem that is becoming more prevalent as technology advances and the use of computer systems grows in comparison to previous generations. Plagiarism is the unauthorized use of another person's work. Since manual plagiarism detection is difficult, this method should be automated. Plagiarism detection can be done using a variety of methods. Some of the research focuses on intrinsic plagiarism, while others focus on extrinsic plagiarism. Data mining is an area that can assist in both detecting plagiarism and improving the reliability of the operation. Plagiarism can be detected using a variety of data mining techniques. Text mining, clustering, bi-grams, tri-grams, and n-grams are some of the techniques that can assist with this. In this paper we will use the data mining techniques to increase the efficiency of detection of plagiarism.
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Nennuri, R., Geetha Yadav, M., Samhitha, M., Sandeep Kumar, S., & Roshini, G. (2021). Plagiarism Detection through Data Mining Techniques. In Journal of Physics: Conference Series (Vol. 1979). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1979/1/012070
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