Аннотация
The work shows that using a Genetic Algorithm (GA), it is possible to solve the following problems: eliminating parallel edges, cycles, loops, duplicating vertices with similar parameters, and other features of the structure of a Computer Ontology (CO) graph. Such CO optimization with the help of GA, for example, of the Information Security (IS) Subject Area (SBA), helps to eliminate logical contradictions that violate the integrity of CO and reduce the efficiency of the functioning and application of the Electronic Textbook (ET). It is also shown that the optimization of the IS SBA CO content is carried out to increase its information richness and ensure adaptation to the information needs of users through a periodic reduction in the volume of the SBA CO to specified limits. The solution was achieved by extracting IS CO elements whose semantic meaning is less than the required one. It has been established that the optimization problem for CO can be reduced to a discrete optimization problem, the algorithms for effective solutions of which using GA are known.