MACHINE LEARNING TECHNOLOGIES OF THE FUNCTIONALLY SUSTAINABLE INTELLECTUAL INFORMATION SYSTEM OF THE INSTITUTION OF HIGHER EDUCATION
DOI: 10.31673/2412-4338.2023.014252
Abstract
Market development has created a need for widely functional integrated corporate information systems that combine data storage databases, analytical tools, and document management systems. In today's conditions, the question of choosing a corporate information system is often a key strategic decision that largely determines the efficiency of the enterprise. Therefore, the development, support and optimization of intelligent information systems is an urgent issue of ensuring optimal decision-making based on the analysis of current situations to achieve a certain goal. For this purpose, the optimization of clustering algorithms of intelligent data analysis based on cloud technologies and machine learning to increase the efficiency of the intelligent information system of a higher education institution is considered.
The choice of the best algorithm under the conditions of a specific task should be reasonably carried out by the person who makes the decision, since the processes of interpretation and evaluation of the obtained results after their analysis are extremely important. At this stage, the main role is played by an expert in the subject field under investigation, who, in addition to using the criteria, can, based on a priori ideas and knowledge of key target indicators, perform additional verification of the results for further decision-making. To achieve the maximum result, a complex approach to data analysis is required, which includes both the use of a priori knowledge of specialists for pre-processing of data and interpretation of results, and the use of specialized algorithms.
The paper analyzed the shortcomings, optimized and parallelized the optimized algorithms in order to improve the ability to process a large array of data and increase the effect of the activity of the intelligent information system of the institution of higher education using cloud computing and machine learning of the intelligent information system.
Keywords: intelligent information system, functional stability, clustering algorithms of intelligent data analysis, machine learning, higher education institution.
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