ABSTRACT
The research is devoted to the study of the problem of planning leisure time during quarantine periods (forced staying at home) using information technology tools. The need for adaptation and modification of the usual forms of leisure activity to the new format has been determined. The methods of providing recommendations were studied. Using the Analytical Hierarchy Method, the optimal type of system for the implementation of the proposed solution was chosen-a recommendation system. The algorithm of the recommendation system, which offers alternatives for spending time during periods of forced staying at home, is described. A weighted hybrid mechanism was used to provide recommendations. The recommendations feature of the developed prototype of the information system is the provision of offers that contain, in addition to passive types of leisure, also active ones that take into account the characteristics of each of its users. © 2022 IEEE.
ABSTRACT
The COVID-19 crisis has speeded up the economy’s digitalization, including artificial intelligence techniques. Artificial intelligence methods are increasingly being implemented into finance from year to year. The research reveals the essence and concept of using artificial intelligence methods in general and in debt financing in particular. It is proposed to distinguish four criteria (context, data, model and tasks) in the concept of using artificial intelligence methods and to consider such usage through the prism of the life cycle of the artificial intelligence system. The list of tasks of artificial intelligence systems in debt financing is formed, and the main problem situations on debt financing management in which it is expedient to use artificial intelligence methods are identified. Since bonds are the primary tool for attracting debt financing in the stock market, and their scope requires the active implementation of digital technologies, the research clarified the algorithm for pricing bonds using artificial intelligence methods, which improves the interaction between lenders and borrowers. Particular attention is paid to identifying the benefits and risks of using artificial intelligence methods in debt financing and applying artificial intelligence methods in debt financing of business entities at different management levels. It is proved that in the conditions of total digitalization, the necessity of using modern information technologies, particularly methods of artificial intelligence, is necessary. © 2022 Copyright for this paper by its authors.
ABSTRACT
Big Data Analysis is used in various spheres. Financial crises, which are an integral part of the modern economy, require new approaches to analysis. The research hypothesizes the existence of a link between financial crises and shocks in foreign exchange (FX) market, and it is proven using Big Data Analysis information technology. The information base of the research was data on exchange rate fluctuations during the financial crises in Ukraine ( 2008, 2015, 2020), as well as similar data on COVID-19 Pandemic Crisis in Ukraine, Russia, Belarus, Georgia and Poland. In the course of the research, data structuring, data visualization, analysis of statistical links and regularities among data series were performed, in particular, using Fstatistics and Student's t-test. The results of the research have showed that the Big Data Analysis makes it possible to identify trends in unstructured and poorly structured data, in particular regarding exchange rate fluctuations.