Node Importance Evaluation of Complex Network Based on M-TOPSIS Method

The importance evaluation of nodes in complex networks is of great significance. Usually, the importance evaluation of nodes can be based on degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, and structural holes, etc. it is more reliable to evaluate the importance of the nodes with multiple indicators. Therefore, based on the principle of multiple attribute decision making (MADM), a new method for evaluating the importance of nodes based on M-TOPSIS is proposed in this paper, this method can be used to evaluate the nodes by using multiple indicators, and it can avoid the typical problems existing in the traditional method based on TOPSIS, such as the problem of inverted order of evaluation value. Experimental results show that the new method based on M-TOPSIS has good reliability and adaptability.