基于属性信息和结构特性的网络节点重要度研究

现有的节点重要度排序方法大多只针对网络的拓扑结构进行研究，忽视了网络节点自身所包含的属性信息.然而这些属性信息至关重要，却广泛存在不完备性，这些不完备属性信息与节点的重要性密切相关.针对这一问题，提出一种基于优势粗糙集理论和TOPSIS方法的网络节点重要度分析方法，融合网络结构特性和节点属性信息，克服了单一从拓扑结构分析的局限.最后，将本文所提出的方法应用于微博社交网络中的用户重要度评价，并与其他方法进行比较，结果表明，该方法的排序结果对节点在属性信息和结构特性的重要性进行了较好的综合，能全面地体现出各节点的重要程度.

Research on the Importance of Network Nodes Based on Attribute Information and Structural Characteristics

Most of the existing node importance ranking methods only study the topology of the network， ignoring the attribute information contained in the network nodes themselves. Attribute information is very important， but there is widespread incompleteness. Incomplete attribute information is closely related to the importance of nodes. Aiming at these problems， a network node importance analysis method based on superior rough set theory and TOPSIS method is proposed， which combines network structure characteristics and node attribute information and overcomes the limitations of single topological structure analysis. Finally， the proposed method is applied to the user importance evaluation in Weibo social network and compared with other methods. The results show that the ranking results of this method can well synthesize the importance of each node in attribute information and structural characteristics and can fully reflect the importance of each node.