In order to identify the node importance more finely and extend the scope and category of effective information gathering of nodes,the spatial location attribute information of network nodes and their direct and indirect neighbor nodes were fused and clustered,a node importance identification method of multi-order neighbor hierarchical association contribution of complex networks was proposed.The definition of the contribution of node level location attributes was given based on the network node spatial location hierarchical differences and inter-layer association information.A complex network target node multi-order neighbor hierarchical association contributions matrix was constructed to characterize the hierarchical contribution of the associations between direct neighbor nodes,indirect neighbor nodes and target nodes to their influence.A node importance identification method that fused node topological location contribution across layers and levels of space with multi-order neighborhood hierarchical association contribution was proposed.The simulation experiments showed that the proposed method could effectively improve the precision and accuracy of node importance identification on six real networks.This study provided a scientific theoretical basis for in-depth exploration of the dynamic evolution mechanism behind the network,and then made prediction and regulation by exploring the multi-order hierarchical interaction behaviors among the network nodes.
关键词
复杂网络/节点重要性辨识/多阶邻居相似度/多阶邻居紧密度/多阶邻居递阶关联贡献度
Key words
complex network/identification of node importance/multi-order neighbor similarity/multi-order neighbor closeness/multi-order neighbor hierarchical association contribution
维普
万方数据