Shabanova-Kushnarenko L. Predicate models, methods and technology of process knowledge treatment in informative systems

Object of research is knowledge processing processes in information systems. The purpose of research is process knowledge models development by log files analyzing using the apparatus of the finite predicates algebra and relational networks and Process Mining and Case-Based Reasoning technologies. Methods of research: apparatus of the finite predicates algebra and relational networks; Case-Based Reasoning; Process Mining; computational mathematics and computer modeling. Theoretical and practical results: the creation of process knowledge processing technologies in information systems based on algebraic and models logical formalization and methods Process Mining and Case-Based Reasoning. The scientific novelty of the work lies in the fact that the improved model predicative metric in the space of a precedent that allows practical test of its existence by means of a system of conditions and the introduction of the Euclidean metric in the space of linearized attributes; first developed a method for evaluating the proximity of precedents based on the tabulation attributes scales and the attribution of weights based on the functional dependence of the weights of the attributes of precedents that can significantly improve the accuracy of estimates of the proximity of precedents by taking into account the real weight of the growth of the attributes in their critical bands; It was further developed a method for constructing a predicate hierarchical model of process knowledge in the form of a relational metaseti, which is based on the model of "data-information-knowledge-wisdom". Layering simplifies the configuration process model and complements its implicit connections; An improved method for configuration of a hierarchical model of process knowledge based on the analysis of log files, which takes the form of a hierarchical system of binary predicates that define the behavior of the logic of the process. The method includes setting a subject area, which increases the efficiency of Process Mining techniques. Degree of implementation: the results obtained during the execution of the thesis, introduced in the Ukrzaliznytsia Central Clinical Hospital (Kharkiv) in the development of software and algorithmic part and filling the knowledge base of software and hardware of automated medical diagnostics complex. The theoretical results of the thesis are introduced in the educational process at the KhNURE Software Engineering Department and at the NTU "KPI" Intelligent Computer Systems Department. Application area are information decision support systems, business processes, data relationships analysis, information retrieval systems.