The problem of merging knowledge graphs (KG) presented in different languages is becoming more and more relevant. The main stage for its solution is the identification of equivalent entities and their descriptions. It is also known as the entity alignment problem. The recent research shows that existing approaches are not effective for all languages. This article presents the experiments aimed at improving the alignment of entities on an English-Russian dataset. The results obtained are considered from the point of view both of the whole graph and of individual types of entities. The influence of the number of relations and attributes on the accuracy of the algorithms is estimated.

This article considers simultaneous attainability of consistency and availability. The approaches to determining the maximum possible levels of accessibility for different consistency models are compared. The necessity of introducing quantitative metrics for these two indicators and review the prior articles with quantitative estimates of consistency is advocated. The importance of this problem is confirmed, and directions for modeling the parameters of the applied problem using numerical experiments are proposed.

This article investigates the problem of experimental study classification problem of scientific text materials by utilizing the methods of Machine Learning and Deep Learning. The experimental study based on text classification method which proposed preprocessing and specificity of scientific text materials by using the ML algorithms to improve accuracy and speed of text classification was conducted. The analysis of indexation and classification methods by specialties was conducted for a set of scientific text materials. The evaluation and comparison of ML algorithms’ quality was considered, and the results of dissertational works’ classification by machine learning methods within the framework of the existing training set of scientific materials were obtained.

In this paper, we consider the problems of modeling and controlling multidimensional inertialess systems with delay under nonparametric uncertainty. We are talking about the multidimensional processes which are in conditions where the form of parametric equations for various channels of the object is absent due to lack of a priori information. The main emphasis is placed on the case when the components of the vector of output variables are randomly connected in an unforeseen way. In the case of a stochastic dependence of the output variables, the mathematical description of the object is reduced to a system of implicit equations, the form of which is unknown. Therefore, the main task of modeling is to find the predicted values of output variables from known input variables. When managing a multidimensional object, an important feature is the definition of setting actions. The main thing here is that the setting influences of the control system should not be chosen arbitrarily from the corresponding areas, but depending on the definition of the previous ones. Nonparametric identification and control algorithms for multidimensional systems are proposed. Computational experiments that show the efficiency of using the proposed nonparametric identification and control algorithms are presented.

This article is devoted to the consideration of the most common sequences of implementation of high-tech projects in the field of mechanical engineering and instrument engineering in the framework of small enterprises. The reasons for the existing restrictions affecting the quality of complex projects are considered. A model of formalization of the field of information transformation of the source data of high-tech projects, which has a significant impact on the expected results, is proposed.

In this paper, an algorithm to import data from the messenger Telegram and to build weighted graphs of interacting objects is described. To import data, the given Telegram-channels are taken as a basis. Then, channels which had any of the recorded three interactions with previous ones are iteractively revealed: common external links, mentions of each other, reposts. Further, the algorithm focuses on the given configuration and uses it to calculate the weights on the edges of the resulting graph. The configuration takes into account the type of interaction of channels with each other. The authors introduce the concept of (U, M, R)-model of information interaction. The authors describe the developed algorithm and implemented software for constructing weighted graphs. The paper shows the example of weighted graph of interacting objects that was built by the described algorithm according to the (U, M, R)-model.