Plagiarism types and detection methods: a systematic survey of algorithms in text analysis
| dc.contributor.author | Makhmutova A. | |
| dc.contributor.author | Turan C. | |
| dc.contributor.author | Amirzhanov A. | |
| dc.date.accessioned | 2025-08-12T06:48:46Z | |
| dc.date.available | 2025-08-12T06:48:46Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Plagiarism in academic and creative writing continues to be a significant challenge, driven by the exponential growth of digital content. This paper presents a systematic survey of various types of plagiarism and the detection algorithms employed in text analysis. We categorize plagiarism into distinct types, including verbatim, paraphrasing, translation, and idea-based plagiarism, discussing the nuances that make detection complex. This survey critically evaluates existing literature, contrasting traditional methods like string-matching with advanced machine learning, natural language processing, and deep learning approaches. We highlight notable works focusing on cross-language plagiarism detection, source code plagiarism, and intrinsic detection techniques, identifying their contributions and limitations. Additionally, this paper explores emerging challenges such as detecting cross-language plagiarism and AI-generated content. By synthesizing the current landscape and emphasizing recent advancements, we aim to guide future research directions and enhance the robustness of plagiarism detection systems across various domains. | |
| dc.identifier.citation | Makhmutova A , Turan C , Amirzhanov A / Plagiarism types and detection methods: a systematic survey of algorithms in text analysis / Frontiers in Computer Science / 2025 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1866 | |
| dc.language.iso | en | |
| dc.publisher | Frontiers in Computer Science | |
| dc.subject | plagiarism detection | |
| dc.subject | AI-generated content | |
| dc.subject | machine learning | |
| dc.title | Plagiarism types and detection methods: a systematic survey of algorithms in text analysis | |
| dc.type | Article |