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2018 | OriginalPaper | Buchkapitel

Reducing Computational Effort for Plagiarism Detection with Approximate String Matching

verfasst von : Tetsuya Nakatoh, Toshiro Minami

Erschienen in: Recent Advances on Soft Computing and Data Mining

Verlag: Springer International Publishing

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Abstract

Currently, a large number of documents are created as digital material and distributed world-wide. Digital materials are easy to publish and copy at a remarkably low cost. As a result, many documents are copied illegally, and this practice is spreading, making plagiarism a significant social issue. Therefore, the need to develop systems that detect plagiarism is very high. We have developed a new plagiarism detection method that compares documents by using approximate string matching to detect plagiarism. We have also developed a technique that reduces the computational time of the comparison method. In this paper, we demonstrate our proposed method’s usefulness through experiments and through the measuring indexes of precision and recall.

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Vorheriges Kapitel Sarcasm Detection Using Features Based on Indicator and Roles

Nächstes Kapitel Weighting of Noun Phrases Based on Local Frequency of Nouns

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Titel: Reducing Computational Effort for Plagiarism Detection with Approximate String Matching
verfasst von: Tetsuya Nakatoh
Toshiro Minami
Verlag: Springer International Publishing
Buch: Recent Advances on Soft Computing and Data Mining
Print ISBN: 978-3-319-72549-9

Electronic ISBN: 978-3-319-72550-5

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-72550-5_41

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