title: ÐÐ²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð¿Ð¾Ð¸ÑÐº ÑÐ¸ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¹ Ð½Ð°ÑÑÐ½ÑÑ Ð¿ÑÐ±Ð»Ð¸ÐºÐ°ÑÐ¸Ð¹ Ð² Ð½Ð°ÑÐºÐ¾Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð±Ð°Ð·Ð°Ñ Ð´Ð°Ð½Ð½ÑÑ , Ð½Ðµ Ð¿ÑÐ¸Ð²ÑÐ·Ð°Ð½Ð½ÑÑ Ðº Ð±Ð¸Ð±Ð»Ð¸Ð¾Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¾Ð¼Ñ Ð¾Ð¿Ð¸ÑÐ°Ð½Ð¸Ñ ÑÐ¸ÑÐ¸ÑÑÐµÐ¼Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Automatic search for citations of scientific publications in scientometric databases that are not linked to the bibliographic description of the cited work
Creators: name: ÐÐ¾Ð³ÑÐ½Ð¾Ð², ÐÐ³Ð¾Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð½ÐµÐ¿ÑÐ¸Ð²ÑÐ·Ð°Ð½Ð½ÑÐµ ÑÐ¸ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ
Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð¿Ð¾Ð¸ÑÐº
Ð½Ð°ÑÐºÐ¾Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ°Ñ Ð±Ð°Ð·Ð° Ð´Ð°Ð½Ð½ÑÑ
Ð±Ð¸Ð±Ð»Ð¸Ð¾Ð³ÑÐ°ÑÐ¸Ñ
unrelated citations
automatic search
scientometric database
bibliography

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description: The topic of the final qualifying work: Â«Automatic search for citations of scientific publications in scientometric databases that are not linked to the bibliographic description of the cited workÂ». This work is devoted to the creation of a search service in the literature lists of scientific articles for lost citations of a given publication. The tasks that were solved during the research: â description of the purpose of the project, its tasks, the final product, and the problem that it solves; â development and effective algorithm for searching for lost citations, superior to the Â«manualÂ» method of searching for lost citations. The development was carried out without Phyton. Within the framework of achieving the formulated goal, tasks were solved, namely: the purpose of the program, its tasks, the final product, and the problem it solves were described; a fast and effective algorithm for searching for lost citations was developed, surpassing the Â«manualÂ» method of searching for lost citations; the service was implemented in the form of a website and a browser extension. The developed program can be improved in the future with the help of machine learning and neural networks. Therefore, the potential application of machine learning and neural networks in the developed program can significantly improve its functionality, efficiency and accuracy of citation analysis.