复杂系统与复杂性科学
複雜繫統與複雜性科學
복잡계통여복잡성과학
COMPLEX SYSTEMS AND COMPLEXITY SCIENCE
2009年
4期
26-33
,共8页
成员角色%CP值%中心性距离%骨干网
成員角色%CP值%中心性距離%骨榦網
성원각색%CP치%중심성거리%골간망
role of members%CP index%centrality distance%backbone
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.
基于成員角色,提齣瞭一種骨榦網挖掘算法,對football,netscience和hep-th等網絡載體進行瞭實驗和數據分析,結果錶明所得到的骨榦網絡能較好體現網絡的骨榦結構特徵.同時提齣瞭一箇骨榦網性能的度量指標--CP值,實驗錶明該指標能較好地權衡骨榦網規模和中心性等度量因素.
기우성원각색,제출료일충골간망알굴산법,대football,netscience화hep-th등망락재체진행료실험화수거분석,결과표명소득도적골간망락능교호체현망락적골간결구특정.동시제출료일개골간망성능적도량지표--CP치,실험표명해지표능교호지권형골간망규모화중심성등도량인소.
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.