Efficient methods are required for plagiarism detection. This paper proposes a fast and scalable method for detecting “copy and paste”-type plagiarism in documents. Implementing detection methods for this type of plagiarism requires a long processing time or a large database for comprehensive matching of ordered word occurrences. The author improved the scalability of an existing fast method based on fast Fourier transform using the idea of the frequency domain filtering. He evaluated the effect of the improvement on accuracy of the plagiarism detection method, and achieved an effective trade-off between the accuracy and the required size of database.
CITATION STYLE
Baba, K. (2018). Filtering Documents for Plagiarism Detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11198 LNAI, pp. 361–372). Springer Verlag. https://doi.org/10.1007/978-3-030-01771-2_23
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