摘要
在复杂网络分析中,中心性分析已经显示出是一种很有价值的方法。它用来检测网络中的关键点以及对网络元素进行排序。为了支撑这种分析,文中讨论了5种中心性方法,并且在一个人工网络和2个实际网络中展示了它们的应用。这些方法的运用显示了在某种网络中有某种较强的关联,但在另一种网络中有较弱的关联。分析表明:对于复杂网络分析,几种方法应当同时考虑。
Centrality analysis is a valuable method for the structural analysis of complex networks. It is used to identify key elements within networks and to rank network elements. To support this analysis five centrality measures are discussed and their applicability is demonstrated on two example networks. The application of these measures shows that some measures correlate strongly in one network and weakly in another. As a result, several measures should be considered for the analysis of complex networks.
出处
《西安科技大学学报》
CAS
北大核心
2010年第1期107-111,共5页
Journal of Xi’an University of Science and Technology
基金
国家自然科学基金重点项目(60933009)
教育部高校博士点基金资助项目(200807010013)
关键词
中心性
中心方法
复杂网络
社会网络
生物网络
centrality
centrality measure
complex networks
social networks
biology networks
