The widespread implementation of intelligent decision support systems (IDSS) is hampered by the lack of methods and technologies for automatically filling the knowledge base during the operation of such systems. This problem is especially acute in the medical field. Its solution lies in the application of automatic planning technologies.
The article outlines the problem of finding meaningful units in electronic text documents and analyzes the main shortcomings of existing approaches of extracting knowledge from textual information. The article is devoted to the study of the peculiarities of the process of construction of logic and linguistic models of electronic text documents, in particular the description and research of the peculiarities of knowledge bases of the system of automated construction of logic and linguistic models of Ukrainian- language text documents.
To assess the achievement of goals in the context of implementing a sustainable development model, we are considering the methodical and applied tools based on the use of the theory of fuzzy sets and the technology of implementing the model of communication between its individual indicators, which should be used in developing scenarios of strategic development of Ukraine
In this paper the important problem of ontology clustering is considered with the purpose of optimization of intelligent data processing in conditions of uncertainty caused by inaccuracy or incompleteness of data in the subject area. The clustering of ontologies is the process of automatic splitting of a set of ontologies into groups (clusters) based on their similarity degree.
The study analyzes the scheme of services for determining the uniqueness of electronic text documents, considered their main characteristics while checking the originality of the article. An author presents structure of the system for comparative analysis of electronic text documents by content, she outlines the operating principle each of its major components.
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