Node importance measurement method based on multi-attribute fusion

Abstract

Finding important nodes in complex networks is an important topic. However, the location information obtained by many previous studies is not sufficient and effective, and the types of attributes applied also have limitations. Based on K-shell and gravity model, this paper proposes a node importance measurement method based on multi-attribute fusion. In this method, the objective, comprehensive evaluation of multiple attributes is obtained by the entropy weight method. Experiments on real networks show that the proposed algorithm can effectively measure the importance of nodes.