Персона: Прохоров, Игорь Вениаминович
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Институт финансовых технологий и экономической безопасности
Институт финансовых технологий и экономической безопасности (ИФТЭБ) Национального исследовательского ядерного университета "МИФИ" готовит кадры в интересах национальной системы по противодействию легализации (отмыванию) доходов, полученных преступным путем, и финансированию терроризма (ПОД/ФТ).
Междисциплинарность образования позволит выпускникам ИФТЭБ НИЯУ МИФИ легко адаптироваться на современном рынке труда и в бизнес-среде.
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Игорь Вениаминович
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- ПубликацияТолько метаданныеDevelopment of an AI Recommender System to Recommend Concerts Based on Microservice Architecture Using Collaborative and Content-Based Filtering Methods(2021) Malynov, A.; Prokhorov, I.; Прохоров, Игорь Вениаминович© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Recommender system is a complex software system primarily intended to select the most relevant content based on user’s personal preferences. In order to achieve the set goal, a number of tasks must be completed, including: track user actions across various devices; get product data from a number of sources and maintaining their currency; consolidate the data; create user and product profiles bases on big data in a real-time mode; select recommendations in cold start and highly sparse data environment; assess the quality of the recommender system. Completion of each specific task must not extend the time to complete other tasks. Users must instantly get the relevant content even if the system is heavily loaded, for example, due to a popular event announcement. A workaround may be to divide the system into independent components with the ability to scale specific services. Microservice architecture examined in this article intends to ensure required flexibility due to asynchronous message exchange via a data bus and other principles offered by SOA concept. Apart from interaction between the components, the article also introduces the results of development of each specific service from asynchronous user action tracker to recommender engine based on the hybrid approach that includes collaborative and content-based filtering methods, and the knowledge-based approach using Artificial Intelligence techniques. Special attention is paid to a subject category with a number of aspects that prevent applying generic approaches to building recommender systems.
- ПубликацияТолько метаданныеClustering of concert and theater events based on their description(2022) Malynov, A.; Prokhorov, I.; Прохоров, Игорь Вениаминович
- ПубликацияТолько метаданныеAnalysis and applicability of artificial intelligence technologies in the field of RPA software robots for automating business processes(2022) Kanakov, F.; Prokhorov, I.; Прохоров, Игорь Вениаминович
- ПубликацияТолько метаданныеApplications of the Knowledge Base and Ontologies for the Process of Unification and Abstraction of the Information System Description(2022) Piskunov, P.; Prokhorov, I.; Прохоров, Игорь Вениаминович© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Nowadays in the development of information systems (IS) the price of implementing a single piece of functionality is becoming less than the price of simplifying of designing, applying existing solutions and adapting technologies. The degree of abstraction of architectural solutions and amount of attention on transition from individual systems to the information landscape also growing. At the same time, the size of systems and the number of template solutions begin to go beyond the processing capabilities of one person. Also, high-level design can be more subjective then functional design. We are trying to solve this by simplifying the work with the representation of the system, its modules or data, by unifying and abstracting the description of the system. Unifying design through some generalizations and rules or creating elaborate notations is not a new idea. But we work with refining of the description itself, not the method of description and automation of translation, additions or changes in the scale (amount details) of the system description. We use semantic libraries, identification patterns and cognitive perception of the person involved in designing. The goal is to create some kind of analytical agent or digital assistant for IS design, capable of taking into account the specifics of a particular organization or subject area, and will learn through simple replenishing databases of rules and templates. Such utilitarian assistant should remove some workload from the architect as well as reduce his subjective influence.
- ПубликацияТолько метаданныеEnhancing Event Selection with ChatGPT-Powered Chatbot Assistant: An Innovative Approach to Input Data Preparation(2024) Malynov, A.; Prokhorov, I.; Прохоров, Игорь Вениаминович