基于成员角色的骨干网挖掘算法

A Backbone Extracting Algorithm Based on Role of Members

基于成员角色,提出了一种骨干网挖掘算法,对football,netscience和hep-th等网络载体进行了实验和数据分析,结果表明所得到的骨干网络能较好体现网络的骨干结构特征。同时提出了一个骨干网性能的度量指标——CP值,实验表明该指标能较好地权衡骨干网规模和中心性等度量因素。

Based on the role of members,we proposed a new backbone network mining algorithm. To validate the performance of the proposed algorithm,we use football network, netscience network and hep-th network as the test-bed. Experimental results show that this algorithm can present the holistic features of complex networks. Moreover,a measurement named CP index is suggested to measure the performance of backbone network,which could tradeoff between the scale of networks and centrality distance.