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Dalian, Liaoning China
June 18, 2008 to June 20, 2008
ISBN: 978-0-7695-3161-8
pp: 569
Plagiarism in texts is issues of increasing concern to the academic community. Now most common text plagiarism occurs by making a variety of minor alterations that include the insertion, deletion, or substitution of words. Such simple changes, however, require excessive string comparisons. In this paper, we present a hybrid plagiarism detection method. We investigate the use of a diagonal line, which is derived from Levenshtein distance, and simplified SmithWaterman algorithm that is a classical tool in the identification and quantification of local similarities in biological sequences, with a view to the application in the plagiarism detection. Our approach avoids globally involved string comparisons and considers psychological factors, which can yield significant speed-up by experiment results. Based on the results, we indicate the practicality of such improvement using Levenshtein distance and Smith-Waterman algorithm and to illustrate the efficiency gains. In the future, it would be interesting to explore appropriate heuristics in the area of text comparison
Zhan Su, Byung-Ryul Ahn, Ki-Yol Eom, Min-Koo Kang, Jin-Pyung Kim, Moon-Kyun Kim, "Plagiarism Detection Using the Levenshtein Distance and Smith-Waterman Algorithm", ICICIC, 2008, Innovative Computing ,Information and Control, International Conference on, Innovative Computing ,Information and Control, International Conference on 2008, pp. 569, doi:10.1109/ICICIC.2008.422
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