Abstract
The issue of article plagiarism has become increasingly important due to research paper plagiarism that have been frequently proclaimed. Previous studies on plagiarism detection have been conducted mainly by using vectors, statistics and matrices methods. However, the plagiarism detection system has been found to fail to correctly locate the plagiarized paragraphs as a result of sentence modification or superfluous words insertion by plagiarists, thereby leading to imprecise detection and ineffective plagiarism prevention. This study used the Chinese word segmentation and SQL intersection operation technique to build a plagiarism checker system to enhance the plagiarism detection precision. For the purpose of the study, an SQL Intersection Operation was introduced for the plagiarism detection, which was proven to be more effective than previous studies which read a massive quantity of words into program variables. This study’s results show higher efficiency and more precision of the plagiarism detection method proposed than the commercial plagiarism-detection software available on the market.
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Ying, MH., Fan, JW., Yu, HM. (2017). A Study of Plagiarism Checker System Based on Chinese Word Segmentation and SQL Intersection Operation Technique. In: Król, D., Nguyen, N., Shirai, K. (eds) Advanced Topics in Intelligent Information and Database Systems. ACIIDS 2017. Studies in Computational Intelligence, vol 710. Springer, Cham. https://doi.org/10.1007/978-3-319-56660-3_34
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DOI: https://doi.org/10.1007/978-3-319-56660-3_34
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