Известия высших учебных заведений. Поволжский регион:Технические науки (Dec 2023)
Representation and structuring of knowledge in the semantic oriented computing environment. Part 2. Interpretations of conceptual event network models for given subject areas
Abstract
Background. Based on the proposed methodology for deep structuring of knowledge in a semantically-oriented intelligent computing environment based on expanding the descriptive capabilities of Petri nets by integrating them with conceptual graphs, a technique for interpreting conceptual event network models for given subject areas is given. The computing environment is understood as a virtual distributed computing system implemented on a global computer network. Like the “Semantic Web”, a conceptual graph integrated with a logical Petri net within a single formalism suitable for subsequent machine processing is chosen as the basis for representing intellectual information about a subject area. The schematic representation of conceptual graphs hides much of the complexity associated with predicate calculus. The presented examples of conceptual graphs with event concepts contain not only a declarative, but also a procedural component of the knowledge representation model. The integration of conceptual graphs with logical Petri nets, considered as a number of examples from various subject areas illustrates a special type of semantic networks. The software through which this integration is implemented within the framework of one knowledge representation model is also described. It is shown that subject areas determine the structuring of computer science itself and its directions of development, which also applies to intelligent systems in particular. The purpose of the study is to automate the selection of facts and inference rules for the subsequent software implementation of this approach in intelligent event systems using the example of specific subject areas of human activity. Materials and methods. The methodological basis for researching the subject area is focused on the use of simulation modeling of intelligent event systems, in which the interactions of components are specified locally. In the general case, the construction of a simulation model of an intelligent event system is based on the analysis of cause-and-effect situational relationships and the rules for modifying both the signature and specific predicates and functions. Results. A method for synthesizing conceptual logical Petri nets are implemented and illustrated with examples based on identifying the general semantics of conceptual graphs and Petri nets, resulting in the construction of models with declarative, imperative and dynamic properties.
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