knowledge base

Context-based methods represent an important part of toolkit used to build intelligent systems. In the article existent definitions of context for a system with a single decision making agent were discussed. Available formal models for context data representation and processing were compared. The approaches for different forms of reasoning within context were analyzed. Also the application of context awareness in systems with situation awareness is discussed. In the article unresolved problems and tasks in the domain of context aware computing are delineated.

In the article the problem of building intelligent agent whose knowledge base core is ontology has been solved. Classification of those systems according to their functioning has been done. For each class appropriate mathematical software has been developed. Intelligent agent models which functioning is based on the ontology has been investigated. The concept of adaptive ontology has been introduced. The model of adaptive ontology is considered as development of the classic model by adding importance weights of the concepts and relations that are stored in the ontology.

In this paper integration of RBAC (Role-based access control) mechanism with an expert system technology for building modern intellectual access control systems is presented. As a result, intellectual access control system is created which if compared to existing systems proposes additionally some automation based on rules in knowledge base and self-teaching.

In this paper mathematical formalization for software system based on ontological models is proposed. Formalization is built using algebraic types system approach. Developed formal representation of models and modeling system.

In this paper we propose a formalization of ontology-based task execution modeling system. It is built using approach of algebraic systems theory. We show that proposed algebraic system is based on multiple domains, which can be used for ontological models representation and knowledge elucidation, storage and processing

In the paper the approach to automated construction of interpretation functions (axioms) of concepts and relations of the domain ontology during its training are considered. The method of recognizing the semantics of natural language texts and its representation in the form of descriptive logic.

The paper aims to study the fuzzy data mining techniques. The emphasis is put on an intelligent analysis of fuzzy knowledge bases and problems that arise. Most popular methods are described, their advantages and results obtained with their assistance are highlighted. Generalized use cases of such methods are given.

In the paper the method of the automatic development of ontology has been developed. A method, algorithm and means for selection of knowledge from the text document is proposed. It is shown that this algorithm has to be multistage and involve hierarchical recognition procedure of concepts, relations, predicates and rules which are included into the resulting ontology.

The importance of ontology within concepts of the knowledge base and intelligent systems is considered in the article. Standard ISO/IEC 25012 has been offered for evaluation of ontologies qualities of knowledge bases of intelligent decision support systems.