Abstract: Node ranking is a promising area in complex networks researches.In this paper,a new node ranking algorithm based on topology potential is presented on the foundation of data field theory in cognitive physics,which can reflect the importance of nodes more precisely.An "axiom set" with natural language is established,which can concisely describes what the importance of node is.The approach of topology potential is more close to the "axiom set" than other approaches.In the end,the nodes are qualitatively partitioned using a hierarchical clustering method based on data fields.