Ways of Classifying Digital Platforms

Abstract

Introduction. Interest in the study of digital platforms (DP) is due to their prevalence and the dependence of this phenomenon on the possibilities of using information technologies. The growing distribution and great potential of the DP is connected not only with the use of new hardware and software, but also with the integration of digital technologies into business processes. The need for a deeper understanding of the differences and similarities of various CPUs prompts researchers to turn to the fundamental mechanism of knowledge organization – classification. From a practical point of view, the classification helps to compare different CPUs and allows users to choose the one that provides the desired results. Formulation of the problem. The problem of CPUs classification is to identify specific and common characteristics for building clusters using different approaches. When modeling and solving the classification problem, static methods and machine learning methods are used. The most widespread of them are the method of nearest neighbors and the method of support vectors. The theory of combinatorial optimization was used to build the mathematical model. The approach proposed. To build a mathematical model of the classification problem, the theory of combinatorial optimization was used, which allows to investigate some properties of this problem. The argument of the objective function in it is the division of the -element set into subsets. This combinatorial configuration can be either with or without repetitions, either finite or infinite. When finding the optimal result, a situation of uncertainty arises, which is related to the structure of the argument of the objective function which is a combinatorial configuration. Conclusion. The classification problem belongs to a broad class of partitioning problems. In it, the characteristics of the clusters are known, the objects that need to be determined, to which class they belong, are analyzed not simultaneously, but by groups or individual elements. Since the result is determined not simultaneously, but by a partial objective function, the classification problem belongs to the dynamic problems of combinatorial optimization. The classification of digital platforms is carried out by heuristic methods, in particular the nearest neighbor method. Both one and a set of common characteristics characteristic of certain CPUs are used as criteria.