Abstract
The importance measurement of nodes in directed weighted networks is of great significance for theoretical research and practical application of networks. Aiming at the directed weighted network model in actual networks, based on the special transformation of graphs and tree roots, this paper proposes a comprehensive quantitative assessment method for the importance index of nodes based on the directed weighted network’s global properties, local attributes, network location and bidirectionally propagation. This method transforms the nodes to be analyzed in the graph to root, constructs a bidirectional depth-affected XD tree and a breadth-affected XB tree with the node to be evaluated as the root of the tree. Then comprehensively consider the two-way influence of the node level, node neighbors and the closeness between neighbors in the two trees constructed, and the in-out effects, build a deep impact evaluation model at the two-way level, two-way neighbor information and comprehensive evaluation index of clustering coefficient. By calculating the comprehensive importance value of each node in the network, the comprehensive ranking of the importance of the nodes in the network can finally be obtained. The robustness experiment of ARPA network shows that the G value of the important node quantified by this method has absolute advantages, this method can effectively analyze key nodes in the network.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call