MODELS OF BUSINESS KNOWLEDGE IN ARTIFICIAL INTELLIGENCE SYSTEMS FOR AN EFFICIENT COMPETITIVE ENTERPRISE

Introduction. Since the main final goal of the processes of intellectual analysis of business data is the extraction/ search/obtainment of new, hidden knowledge in the form of patterns/regularities (with the aim of further automated use of this new knowledge in corporate artificial intelligence systems) — it is important and urgent to investigate the complex of problems of effective and optimal formalization, configuration and parameterization of taxonomized knowledge representation models. In addition, it is worth noting that corporate knowledge bases in themselves are one of the most important resources of a modern enterprise, and the effective use of this resource can significantly affect its competitiveness, investment attractiveness and capitalization. In other words, the management of corporate knowledge bases is a technological process of working with the information resources of the enterprise to ensure access, extraction and analysis of corporate information, which gives users the opportunity to navigate in huge stores of structured and unstructured information of the enterprise, and, using existing knowledge, make faster decisions on based on more complete information. Purpose. The main goal of this study is to investigate the issues of effective search, formalization and use of knowledge within the framework of effective and competitive enterprise management. This main goal of the research is implemented through the following sub-tasks of the research: analysis of the concept of knowledge as an important corporate asset; improvement of the complex taxonomy of corporate knowledge; research on the relevance of periodic Data Mining as the main source of new, hidden, non-trivial regularities/patterns in large corporate data in conditions of instability and crisis; study of features, advantages and disadvantages of four main types of knowledge representation models in artificial intelligence systems; justification of the methodology of the hybrid use of different models of knowledge presentation in the design of Knowledge Bases of artificial intelligence systems. Materials and methods. The research materials are: 1) the author's experience, the author's heuristics, accumulated during the implementation of specific projects and in the financial management of effective and competitive enterprises in various sectors of the economy; 2) works of domestic and foreign authors conducting scientific and practical research in the field of data mining; 3) works of domestic and foreign authors conducting scientific and practical research in the field of designing and using knowledge bases for artificial intelligence systems. In the process of carrying out the research, the following scientific methods were used: theoretical generalization and grouping (for research and analysis of the concept of knowledge as an important corporate asset; improvement of the complex taxonomy of corporate knowledge); formalization (study of the specifics of periodic Data Mining as the main source of new, hidden, non-trivial regularities/patterns in large corporate data in conditions of instability and crisis); analysis and synthesis (to study the features, advantages and disadvantages of four main types of knowledge representation models in artificial intelligence systems); logical generalization of the results (justification of the methodology of the hybrid use of different models of knowledge presentation when designing Knowledge Bases of artificial intelligence systems and for formulating conclusions).