Architecture and method of integrating information and knowledge on the basis of the ontological structure

Abstract

The article considers the problem of information and knowledge integration and representation, which is related to a set of following sub-problems: the development of knowledge bases containing decision support rules and precedents; the development of object, ontological, fuzzy, semantic and analytical models to implement decision support processes; the development of modules to select models and to build decisions with the use of knowledge bases; the development of mathematical and simulation models. System analysis methodology states that automated decision of non-structured problems requires reducing them to structured problems by an expert. The research aims to develop universal models of intelligent accumulation and integration of knowledge while formalizing search semantics and decision support. In that context, architectures and methods used to reduce non-structured problems to structured ones are of a great interest. Let us state, that formalization of knowledge structuring processes is required to conduct system analysis of non-structured problems of accumulation and integration of knowledge from distributed heterogeneous sources. This problem is considered as classic artificial intelligence problem involving analysis of multi-disciplinary connections of different subject areas, on the basis of researching the model of semantic relations between knowledge elements. In creating intelligent systems of knowledge management, integration of simulation modeling, theory of agents and ontology building can establish the basis for such systems self-organization and effectiveness.