Yugra State University BulletinYugra State University Bulletin1816-92282078-9114Yugra State University5962410.17816/byusu2020347-52Research ArticleDevelopment of a multi-agent intelligent system for solving problems of classification and ranking of materials on the InternetBurlutskyVladimir V.<p>Head of the Center of Information and Analytical Systems</p>burlutskyvv@uriit.ruKeramovNizam D.<p>Programmer of the Center of Information and Analytical Systems</p>KeramovND@uriit.ruBaluevVladimir A.<p>Programmer of the Center of Information and Analytical Systems</p>BaluevVA@uriit.ruIzertMansur I.<p>Programmer of the Center of Information and Analytical Systems</p>IzertMI@uriit.ruYakimchukAlexander V.<p>Lead Programmer of the Center of Information and Analytical Systems</p>YakimchukAV@uriit.ruUgra Research Institute of Information Technologies2810202016347522801202128012021Copyright © 2020, Burlutsky V.V., Keramov N.D., Baluev V.A., Izert M.I., Yakimchuk A.V.2020<p><em>The article proposes an architectural solution for intelligent information systems based on a multi-agent approach and microservice architecture. An example of using the described solution in the development of an automated intelligent search system that solves the problem of thematic classification and ranking of various sources of information on the Internet is given. The advantages and disadvantages of the developed architectural solution are described.</em></p>multi-agent systemsmicroservicesmachine learninginformation extractiondata processingclassificationrankingмультиагентные системымикросервисымашинное обучениеизвлечение информацииобработка данныхклассификацияранжирование[Grishman, R. Information Extraction / R. Grishman // The Handbook of Computational Linguistics and Natural Language Processing / editors: A. Clark, C. Fox, S. Lappin. – WileyBlackwell, 2010. – P. 515–530.][Кошур, В. Д. Реализация мультиагентной системы искусственного интеллекта для решения задачи классификации / В. Д. Кошур, В. И. Рожков. – Текст : непосредственный // Нейроинформатика-2019 : материалы международной научно-технической конференции. – Москва : Изд-во МФТИ, 2019. – Ч. 1. – С. 24–31.][Lean, Yu. A Multi-Agent Neural Network System for Web Text Mining // Yu Lean, W. Shouyang, Lai Kin Keung // Emerging Technologies of Text Mining. – 2007. – Режим доступа: https://www.researchgate.net/publication/314457104_A_MultiAgent_Neural_Network_System_for_Web_Text_Mining (date of request: 07.10.2020).][Camara, M. A Multi-Agent System with Reinforcement Learning Agents for Biomedical Text Mining / M. Camara, O. Bonham-Carter, J. Jumadinova // Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics. – Atlanta, 2015. – P. 634–643.][A Multi-Agent Architecture for Data Analysis / G. Lombardo, P. Fornacciari, M. Mordonini [et al.] // Future Internet. – 2019. – № 11. – P. 1–12.][Weiss, G. Multiagent systems: a modern approach to distributed artificial intelligence / G. Weiss. – Cambridge : MIT Press; 1999. – 585 p.][Wooldridge, M. An Introduction to MultiAgent Systems / M. Wooldridge. – 2nd edition. – Chichester, England : John Wiley & Sons, 2009.][Ньюмен, С. Создание микросервисов / С. Ньюмен. – Санкт-Петербург : Питер, 2016. – 304 с. – ISBN 978-5-496-02011-4. – Текст : непосредственный.]