Fuzzy Conceptual Graphs for Knowledge Representation in Process-Oriented Organizations

The use of fuzzy conceptual graphs for representing knowledge in process-oriented organizations is considered. Two types of knowledge, procedural and declarative, are discussed; the difference between them is shown along with representation and usage details in knowledge bases. A formal definition of fuzzy conceptual graphs is given, and their ability to represent declarative and procedural domain knowledge in a simple and understandable way is shown. The structure of the knowledge base includes three levels: an ontological layer, which contains concepts and integrates declarative and procedural knowledge; a middle or interface layer, which describes business processes based on real data; and the ground layer, the layer of real (historical) data, which collects primary information about the current state of objects and the relationships between them. The difference between the types of information on each of the layers of the knowledge base is shown, as well as the application method of fuzzy conceptual graphs on the interface layer. A description of the mechanisms of interaction and rules for reflecting data from the ground layer to the interface layer is provided. Mathematical methods for analysis of primary data and fuzzy knowledge indicators are described, which aid in decision-making, optimization and refinement of procedural knowledge systems.

Fuzzy conceptual graphs, knowledge representation, business process, knowledge base, ontology, intelligent agent