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This paper presents the results of analyzing the time load of stations in bike-sharing systems using temporal networks. Temporal networks have many applications in the study of the behavior of complex dynamic systems that have a network structure. In particular, they can be used to analyze and predict many dynamic indicators of transport networks, for example, such as the intensity of transport and passenger flows, traffic congestion, capacity of transport nodes, turnover of vehicles, etc. In this work, the indicators of the centrality of stations and clusters of a bike-sharing network are estimated using temporal networks. Based on the obtained estimates, visual models (Heat maps and Time Series) are constructed to demonstrate the spatial and temporal features of the bike network in a clear and compact form. The station centralities are estimated on the basis of the betweenness measure, and the cluster centralities are estimated on the basis of the Freeman centralization. Experiments confirming the applicability of the built models are conducted using open data from the CitiBike New York system for April 2019. They demonstrated the presence of daily and monthly patterns among both individual stations and more large station clusters.

The paper presents the development results of computer methods for analyzing text data and assessing classification inaccuracies at the stages of thematic modeling. This study uses as an example the task to process textual data of a collection of graduate qualification works prepared and defended by students of Altai State University, Faculty of Mathematics and IT in recent years.
The main results obtained in the paper are listed as follows. Relevant application areas and directions for computer methods and thematic modeling in the educational process are identified. Justification of the general algorithm for solving the problem of the thematic analysis of collections of educational materials is carried out. Information technologies for thematic modeling are developed, and estimation of analysis errors on a set of test documents is obtained. It is shown that computer-based methods of thematic modeling and information technology to support them can be used both in the educational process and in the development of educational and methodological documents.