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A Percentile Transition Ranking Algorithm Applied to Binarization of Continuous Swarm Intelligence Metaheuristics Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Reducing Computational Effort for Plagiarism Detection with Approximate String Matching

Authors : Tetsuya Nakatoh, Toshiro Minami

Published in: Recent Advances on Soft Computing and Data Mining

Publisher: 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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Metadata
Title
Reducing Computational Effort for Plagiarism Detection with Approximate String Matching
Authors
Tetsuya Nakatoh
Toshiro Minami
Copyright Year
2018
Book
Recent Advances on Soft Computing and Data Mining

Print ISBN: 978-3-319-72549-9

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

Copyright Year: 2018

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

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