Detection of plagiarism in scientific texts based on text blocking and cosine similarity criteria

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Majma Negar; Bashtin Sara

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: SOFT COMPUTING Year:2022 | Volume:11 | Issue:1 Page(s): 0-0

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Information Journal Paper

Title

Detection of plagiarism in scientific texts based on text blocking and cosine similarity criteria

Author(s)

Majma Negar | Bashtin Sara

Keywords

Plagiarism

Recognizing the authenticity of scientific texts

Cosine distance

Block text

Text processing

Abstract

In the last decade, with the expansion of the World Wide Web, the speed and ease of access to ideas, documents, articles, manuscripts, and data collected by others has increased. This has made the exchange of information and ideas between researchers and producers of science easier, but on the other hand, it has made it easier to apply unauthorized copies, write summaries without mentioning the source, and steal literary texts in general. Since universities and educational centers make scientific and research resources easily available to most users, recognizing the authenticity of scientific texts in these centers is more important and, of course, more sensitive. In this research, a method is presented to compare the related parts using the blocking of document parts. In the proposed method, after classifying the documents into two categories of main documents and suspicious documents, preprocessing has been done with the aim of eliminating word stops and new wording. Then the documents are segmented and using cosine similarity, the degree of similarity of the texts with each other is determined. The proposed method in the test of 50 documents in the data set has an accuracy of 94%, which is an improvement of 2% compared to one of the similar methods.

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APA: Copy

Majma, Negar, & Bashtin, Sara. (2022). Detection of plagiarism in scientific texts based on text blocking and cosine similarity criteria. SOFT COMPUTING JOURNAL, 11(1 ), 0-0. SID. https://sid.ir/paper/1041346/en

Vancouver: Copy

Majma Negar, Bashtin Sara. Detection of plagiarism in scientific texts based on text blocking and cosine similarity criteria. SOFT COMPUTING JOURNAL[Internet]. 2022;11(1 ):0-0. Available from: https://sid.ir/paper/1041346/en

IEEE: Copy

Negar Majma, and Sara Bashtin, “Detection of plagiarism in scientific texts based on text blocking and cosine similarity criteria,” SOFT COMPUTING JOURNAL, vol. 11, no. 1 , pp. 0–0, 2022, [Online]. Available: https://sid.ir/paper/1041346/en

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