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The process of automated development of base ontology is considered. It has been offered to consider the concepts and elements of ontologies for increasing the effectiveness of knowledge bases, the core of which is the ontology. Methods of specifying the weights of the relevant elements and optimization the structure of knowledge base of ontologies has been elaborated. The basic idea is that new knowledge is a refinement of the plan (i.e. optimal strategy) of an intelligent agent behavior. Such plan forms a skeleton of agent`s knowledge base (its ontology), implemented using some formal language. This work describes approach to the decision support intelligent systems development based on ontologies as part of such systems knowledge bases. Such systems are classified in terms of their functioning based on ontologies. Mathematical functioning of decision support intelligent systems is developed, which is based on ontologies. The term adaptive ontology is introduced to denote that. The adaptive ontology model is defined as classic model development by adding weights of importance of concepts and relations, stored in ontology.
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Victoria Vysotska, PhD, Associate Professor of Information Systems and Networks (ISN) Department at Lviv Polytechnic National University (LPNU), Deputy Head of ISN Department, Lviv, Ukraine. Vasyl Lytvyn, Professor, Head of Information systems and networks Department at Lviv Polytechnic National University, Lviv, Ukraine.
