基于多属性决策的复杂网络节点重要性综合评价方法

复杂网络中的节点重要性评价在实际应用中有着重要意义.现有的一些重要性评价指标如度、介数等存在适用范围有限,评价结果不够全面等缺点,因为节点在复杂网络中的重要性不仅仅受单一因素的影响.为此,本文提出了一种基于多属性决策的复杂网络节点重要性综合评价方法.该方法将复杂网络中的每一个节点看作一个方案,其多个重要性评价指标作为该方案的属性,通过计算每个方案到理想方案的接近程度,最终得到该节点的重要性综合评价结果.该方法不仅可以用于不同类型复杂网络的节点重要性评价,而且便于扩展,实验结果表明了该方法的有效性.

Key nodes in complex networks identified by multi-attribute decision-making method

In complex networks, it is significant how to rank the nodes according to their importance. Most of the existing methods of ranking key nodes (e.g. degree-based, betweenness-based) only consider one factor but not the integration of whole complex network in evaluating the importance of nodes, so those methods each have a limited application range. In this paper, a multi-attribute decision-making method to identify the key nodes in complex networks is proposed. In our method, each node is regarded as a solution, and each importance evaluation criterion as one solution's attribute. After that, we calculate the closeness between each solution and the ideal solution in order to obtain the integration results of node importance in complex networks. The proposed method can be used in a variety of complex networks. It is also easy to evaluate the importance evaluation criteria. Finally, experimental results show that the proposed method is effective.