New Approach to Plagiarism Detection Using Cellular Learning Automatons and Semantic Role Labeling

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YAGHOBI REZVAN; Yaghobi Mahdi; khotanloue Hassan

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Journal Paper

Paper Information

Journal: JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES Year:2021 | Volume:9 | Issue:36 Page(s): 183-208

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Information Journal Paper

Title

New Approach to Plagiarism Detection Using Cellular Learning Automatons and Semantic Role Labeling

Author(s)

YAGHOBI REZVAN | Yaghobi Mahdi | khotanloue Hassan | Issue Writer Certificate

Keywords

Plagiarism Detection

Cellular Learning Automata

Semantic Role Labeling

Semantic Similarity

Abstract

Plagiarism is removal and to put it in their own name the ideas or words of others. With the Increasing progress of the Internet and the proliferation of online articles, scientific theft has also become easier. Many systems have been developed today to detect plagiarism. Most of these systems are based on lexical structure and string matching algorithms. Therefore, these systems can hardly detect recovery robberies, placement of synonyms. This paper presents a method for identifying plagiarism based on Semantic Role Labeling and Cellular Learning Automata. In this paper, Cellular Learning Automata are used to locate the processed words. Semantic Role Labeling specifies the role of words in sentence. Comparison operations are performed for all sentences of the original text and suspicious text. Results of the experiments on PAN-PC-11 corpus demonstrate the proposed method improves values of evaluation parameters such as recall, precision and F-measure, comparing to previous approaches in Plagiarism Detection.

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APA: Copy

YAGHOBI, REZVAN, Yaghobi, Mahdi, & khotanloue, Hassan. (2021). New Approach to Plagiarism Detection Using Cellular Learning Automatons and Semantic Role Labeling. JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES, 9(36 ), 183-208. SID. https://sid.ir/paper/1030778/en

Vancouver: Copy

YAGHOBI REZVAN, Yaghobi Mahdi, khotanloue Hassan. New Approach to Plagiarism Detection Using Cellular Learning Automatons and Semantic Role Labeling. JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES[Internet]. 2021;9(36 ):183-208. Available from: https://sid.ir/paper/1030778/en

IEEE: Copy

REZVAN YAGHOBI, Mahdi Yaghobi, and Hassan khotanloue, “New Approach to Plagiarism Detection Using Cellular Learning Automatons and Semantic Role Labeling,” JOURNAL OF BUSINESS INTELLIGENCE MANAGEMENT STUDIES, vol. 9, no. 36 , pp. 183–208, 2021, [Online]. Available: https://sid.ir/paper/1030778/en

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