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MAIN PAGE > Journal "Security Issues" > Contents of Issue № 03/2023
This issue is currently being formed. All articles presented on this page have already been included in this issue, are considered published, and will remain unchanged in the final version of the issue along with other metadata of the articles.
Учредитель: Даниленко Василий Иванович, w.danilenko@nbpublish.com
Главный редактор: Шульц Владимир Леопольдович, Doctor of Philosophy, cona01@yandex.ru
Contents of Issue № 03/2023
Informational support of national security
Nikitin P.V., Gorokhova R.I., Bakhtina E.Y., Dolgov V.I., Korovin D.I. - Algorithms for extracting information from problem-oriented texts on the example of government contracts pp. 1-10



Abstract: The research is aimed at solving the problem of the execution of government contracts, the importance of using unstructured information and possible methods of analysis to improve the control and management of this process. The execution of government contracts has a direct impact on the security of the country, its interests, economy and political stability. Proper execution of these contracts contributes to the protection of national interests and ensures the security of the country in every sense. The object of research is algorithms used to extract information from texts. These algorithms include machine learning technologies and natural language processing. They are able to automatically find and structure various entities and data from government contracts. The scientific novelty of this study is the accounting of unstructured information in the analysis of the execution of government contracts. The authors drew attention to the problem-oriented texts in the contract documentation and suggested analyzing them with numerical indicators to assess the current state of the contract. Thus, a contribution was made to the development of methods for analyzing government contracts by taking into account unstructured information. The proposed methods for analyzing problem-oriented texts using machine learning. This approach can significantly improve the evaluation and management of the execution of government contracts. The results of the interpretation of problem-oriented texts can be used to optimize the risk assessment model for the execution of a government contract, as well as to increase its accuracy and efficiency.
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