Персона: Черкасский, Андрей Игоревич
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Институт международных отношений
Цель ИМО и стратегия развития - системная подготовка высококвалифицированных кадров, способных решать нестандартные задачи при реализации международных научно-технологических и торгово-промышленных проектов для компаний и корпораций ключевых секторов экономики страны.
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- ПубликацияОткрытый доступMethods for identifying an information object in social networks(2021) Cherkasskaya, M.; Cherkasskiy, A.; Artamonov, A.; Leonova, N.; Черкасский, Андрей Игоревич; Артамонов, Алексей Анатольевич; Леонова, Наталия Михайловна© 2020 Elsevier B.V.. All rights reserved.Social networks are a unique phenomenon in which a large amount of unstructured information about various users is collected. The collected data can be used to identify different groups of users for the purpose of delivering targeted information to them. The article discusses the issues of building models of thematic groups of users based on multi-criteria assessment and using agent technologies of information collection and processing. The implementation of this method expands the possibilities of social research and the formation of thematic user groups for monitoring and analyzing situations in various areas of human activity. The proposed concept has shown its effectiveness on the training and control sample of objects, which makes it possible to predict the effectiveness of the use of agent technologies for scanning information resources of social media.
- ПубликацияТолько метаданныеMultiagent information technologies in system analysis(2019) Inkina, V. A.; Antonov, E. V.; Artamonov, A. A.; Ionkina, K. V.; Tretyakov, E. S.; Cherkasskiy, A. I.; Антонов, Евгений Вячеславович; Артамонов, Алексей Анатольевич; Ионкина, Кристина Вячеславовна; Черкасский, Андрей ИгоревичCopyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).Agent technologies currently play an increasingly important role in the information technology industry given its ability to learn and evolve, to solve information management problems, to employ data visualization and many other benefits. As a computer program, an agent deals with a challenge Internet users face every single day: to obtain reliable and effective data in the specific thematic field. Multiagent system consists of two or more autonomous agents and aimed at solving complex problems, such as Big Data, Data mining, primary structured and unstructured information processing (including text, numbers and multimedia types of data).
- ПубликацияТолько метаданныеMECHANISMS for IDENTIFYING the PATTERNS of the DYNAMICS of SCIENTIFIC and TECHNICAL PUBLICATIONS on the EXAMPLE of the THEMATIC DIRECTION "ROBOTICS"(2021) Cherkasskaya, M.; Cherkasskiy, A.; Pronicheva, L.; Черкасский, Андрей Игоревич; Проничева, Лариса ВладимировнаCopyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).Scientific activity is a source of new knowledge and the creation of the latest technologies to improve the quality of life. The results of research are presented in the form of articles published in scientific journals or collections of scientific conferences, thereby being the main channel of communication in the scientific environment, and also characterize the state of the scientific organization and the country in the world scientific ranking. The article analyzes the world publication activity of countries on the example of the direction - "Robotics" based on the data of the Web of Science system. It was revealed that the development of technologies is subject to certain laws and it is possible to build predicative models for the emergence of new technologies.
- ПубликацияТолько метаданныеUser Group Classification Methods Based on Statistical Models(2022) Cherkasskaya, M. V.; Cherkasskiy, A. I.; Artamonov, A. A.; Galin, I. Y.; Черкасский, Андрей Игоревич; Артамонов, Алексей Анатольевич; Галин, Илья Юрьевич© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The fundamental difficulty of building an information model of a target object in social networks is that a large number of characteristics (several tens) are used in the description of objects in social networks, described by all conceivable types of data: numbers, score estimates of qualitative characteristics, texts, symbols, video and audio information. Obviously, such non-additive data types cannot be used to construct any integral criterion for the specification of the target object. To solve this problem, the article introduces the concept of “vector of target search”. The general idea for solving this problem, proposed by the authors, is to convert physical characteristics into relative dimensionless quantities with normalized values from 0 to 1. The authors have implemented modern promising ideas in the development of intelligent information technologies, such as: computer training of intelligent agents using illustrative examples from the training sample, agent-based technologies for working with Big Data, the method of wave scanning of social networks when searching for target objects. The implementation of wave scanning of social networks during agent search of targets significantly reduces the computing power required to implement the search process and reduces the amount of “noise” in agent collections. Authors developed a method of marking a single object of a social network to solve the problems of streaming classification of objects in the interests of various groups of researchers, including solving the problems of targeted attraction of applicants to a higher educational institution.