| Title: | Research and Development of Plagiarism Detection Methods Based on Deep Neural Networks |
| Authors: | Nguyen, L. T. |
| Keywords: | материалы конференций;рlagiarism detection;deep neural networks;machine learning;natural language processing;educational technology;semantic analysis;pattern recognition |
| Issue Date: | 2026 |
| Publisher: | БГУИР |
| Citation: | Nguyen, L. T. Research and Development of Plagiarism Detection Methods Based on Deep Neural Networks / L. T. Nguyen // Информационная безопасность : сборник материалов 62-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 13–17 апреля 2026 г. / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: С. В. Дробот (гл. ред.) [и др.]. – Минск, 2026. – С. 46–48. |
| Abstract: | This paper presents a comprehensive review of plagiarism forms in academia, including copy-paste, paraphrasing, mosaic, and idea plagiarism. It analyzes challenges posed by automatic paraphrasing tools, cross-language plagiarism, and multi-source plagiarism. The limitations of traditional detection methods such as string matching, n-gram, and TF-IDF are evaluated. Modern approaches based on deep learning (RNN, LSTM, BERT) and stylometry are discussed, leading to the formulation of a plagiarism detection problem that integrates semantic understanding and stylistic analysis. |
| URI: | https://libeldoc.bsuir.by/handle/123456789/63759 |
| Appears in Collections: | Информационная безопасность : материалы 62-й научной конференции аспирантов, магистрантов и студентов (2026)
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