Complex Network Based Knowledge Graph Ontology Structure Analysis

Ontology is the core of knowledge graph. Traditional ontology description and ontology representation rely on ontology descriptional language. This kind of representation method makes it difficult for people to quickly grasp ontology’s structure and then reuse it or segment it. To solve this problem, we proposed a method to transform ontologies into complex networks. This paper analyses ontologies’ structural characteristics through ontology visualization and ontologies’ degree distribution, clustering coefficient, average path length and eigenvector centrality. We observed that many ontologies have tree-like structures. Our analyses further revealed that a concept’s importance is positively related to its degree and eigenvector centrality. Experiments in university ontology shows that our method has a good effect in intuitively understanding the ontology structure.