The schemes for modeling complex integrated semantic structures and describing the content of knowledge do­mains by embedding these structures into ontologies of such areas are investigated. Such schemes are implemented as descriptions of processes operating with special classes of abstract and subject knowledge. Abstract knowledge classes allow the representation of the content of a knowledge domain using abstract knowledge structures. In intel­ligent systems, such structures are constructed by operations within the knowledge synthesis processes. A unified format of semantic hierarchy formalisms is used to represent content fragments. To construct structures within abstract classes of structures, special relations are defined. That allows the formation of complex knowledge structures in ontologies. Individual subject knowledge represents a designation of a certain entity or a formal description of a property, which is used as an element of the semantic structure of a knowledge domain. Such knowledge forms classes of subject knowledge in ontologies, which allow one to adapt elements of abstract structures to the content of knowledge domains. The applying of abstract structures in ontologies of knowledge domains allows the development of algorithms for the processes of analysis and synthesis of complex objects presented at the abstract level of the ontology. Relations between classes of abstract and subject knowledge within an ontology allow complex semantic structures to be included in ontologies. This allows us to develop algorithms for the implementation of cognitive goals and thought processes based on the synthesis of semantic structures from elements of knowledge domain ontologies. The article presents an analysis of unified structures for abstract knowledge classes in ontologies used to represent certain types of complex entities in subject areas. Descriptions of such entities are given for several general cases of ontologies. In these cases, the embedding of complex semantic representations into knowledge domain ontologies is applied. The indicated cases are associated with the processes of knowledge synthesis, which represent the implementation of cognitive goals. The paper presents examples of classes and relationships in ontologies of abstract and subject knowledge, providing solutions to professional problems: of managing the synthesis of complex objects, achieving the goals of complex systems, as well as developing areas of knowledge based on the evolution of ideas about the content and essence of such areas. Application of the proposed principles and approaches to modeling intelligent systems as subjects of knowledge areas operating within the framework of such areas is introduced.

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