Meta-Analysis of Cross-Language Plagiarism and Self-Plagiarism Detection Methods for Russian-English Language Pair

被引:0
|
作者
Tlitova, Alina [1 ]
Toschev, Alexander [1 ]
Talanov, Max [1 ]
Kurnosov, Vitaliy [2 ]
机构
[1] Kazan Fed Univ, Higher Inst Informat Technol & Intelligent Syst, Comp Engn Dept, Kazan, Russia
[2] Kazan Natl Res Technol Univ, Inst Polymers, TPPKM Dept, Kazan, Russia
来源
基金
俄罗斯基础研究基金会;
关键词
cross-language plagiarism; plagiarism detection methods; self-plagiarism detection; text borrowings; multilingual plagiarism;
D O I
10.3389/fcomp.2020.523053
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Scientists need to publish the results of their work to remain relevant and in demanded. The well-known principle of "publish or perish " often forces scientists to pursue an increase in quantity, not quality. Along with the problems of authorship, paid research, fabrication of results, plagiarism, and self-plagiarism are among the most common violations. Their impact is more subtle but no less destructive for the scientific community. Statistics show that the reuse of texts in different languages is very common in various studies. Identification of translated plagiarism is a complex task, and there are almost no such tools for this purpose on the Russian market now. In this article, we have provided an overview of the existing methods for the identification of cross-language borrowings in the scientific articles of the authors. We analyzed solutions by studying the works on various language pairs and paid the great attention to the Russian-English language pair.
引用
收藏
页数:10
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