On the Behaviors of Fuzzy Knowledge Graphs

A knowledge graph is a common artificial intelligence technology, but we may meet some fuzzy semantics that knowledge graphs cannot effectively solve. Inspired by the fuzzy resource description framework (RDF) proposed by Ma and Li [7], we continue studying knowledge graphs in the framework of the fuzzy setting. Specifically, we first refine fuzzy knowledge graphs and their behaviors. An algorithm for calculating the path in fuzzy knowledge graphs is then provided. Next, the closure properties of the collection of the behaviors of fuzzy knowledge graphs are concentrated on under some familiar operations. Second, the commutative property and associative property of fuzzy knowledge graphs are introduced. Finally, the graph patterns, fuzzy selection operations, and fuzzy projection operations are introduced, demonstrating that these two operations also satisfy the associative and distributive properties. The behavior of fuzzy knowledge graphs provides theoretical support for the practical application of fuzzy knowledge graphs and more application values can be discovered on the basis of the properties of fuzzy knowledge graphs in the future.