A Novel C-LeaderRank Nodes Ranking Algorithm Considering Local Clustering Coefficient

As an enhancement of the PageRank algorithm, the LeaderRank algorithm has benefit in complex network node ranking to discover the hub nodes. Based on the traditional LeaderRank algorithm, we propose a C-LeaderRank algorithm in this paper by considering the node clustering coefficient on information dissemination can identify the hub nodes in the crucial position of a complex network. Then, based on the actual port logistics data, a complex port-type logistics city network is established in this paper by applying a new proposed comprehensive evaluation method and the gravity model. Finally, several node ranking algorithms are used for comparison in the complex port-type logistics city network. The results show that the algorithm proposed in our paper has higher effectiveness and greater practical significance.