In recent years, Plagiarism has been easier through increasing development of internet and online papers. Plagiarism is to reuse or copy a text without referencing to the original author. Plagiarism or fraud in schools and universities will be a stimulating factor for researchers. If plagiarism was not identified correctly, cheaters and Plagiarists could get results that are not deserved.This paper presents a method based on the semantic role labeling (SRL) and Genetic Algorithm (GA). The Proposed method works on English texts. Results of the experiments on PAN-PC-9 corpus demonstrate that the proposed method improves values of evaluation parameters such as recall, precision and F-measure, comparing with previous approaches in plagiarism detection.
yaghobi, R., & ختن لو, . (2015). Plagiarism detection in the scientific papers using semantic role labeling and Genetic algorithm. Electronics Industries, 6(3), 67-80.
MLA
rezvan yaghobi; حسن ختن لو. "Plagiarism detection in the scientific papers using semantic role labeling and Genetic algorithm". Electronics Industries, 6, 3, 2015, 67-80.
HARVARD
yaghobi, R., ختن لو, . (2015). 'Plagiarism detection in the scientific papers using semantic role labeling and Genetic algorithm', Electronics Industries, 6(3), pp. 67-80.
VANCOUVER
yaghobi, R., ختن لو, . Plagiarism detection in the scientific papers using semantic role labeling and Genetic algorithm. Electronics Industries, 2015; 6(3): 67-80.
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