| 基于最小社团链接度增量的社团结构挖掘算法 |
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| 引用本文： | 王立敏,高学东,武森. 基于最小社团链接度增量的社团结构挖掘算法[J]. 北京科技大学学报, 2009, 31(1) |
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| 作者姓名： | 王立敏 高学东 武森 |
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| 作者单位： | 1. 北京科技大学经济管理学院,北京,100083;北京科技大学中国教育经济信息网管理中心,北京,100083
2. 北京科技大学经济管理学院,北京,100083 |
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| 基金项目： | 教育部新世纪优秀人才支持计划资助项目(No.NCET-05-0097) |
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| 摘 要： | 针对复杂网络社团结构挖掘算法复杂度高的问题,定义了一个衡量局部社团结构的指标,提出了一种基于最小社团链接度增量的社团结构挖掘算法.本算法的时间复杂度为O(kd),其中d为网络的平均节点度数,k为搜索的节点数.为了验证本算法的性能和计算的准确性,把本算法与一种经典的挖掘局部社团结构方法——Clauset算法,进行了比较.实验结果表明:本算法抽取的社团结构与Clauset算法相比基本一致,但在性能上有了显著提高.
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| 关 键 词： | 复杂网络 链接度 社团结构 挖掘算法 |
Mining algorithm of community structure based on the minimal increment of link degree of a community |
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| WANG Li-min,GAO Xue-dong,WU Sen. Mining algorithm of community structure based on the minimal increment of link degree of a community[J]. Journal of University of Science and Technology Beijing, 2009, 31(1) |
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| Authors: | WANG Li-min GAO Xue-dong WU Sen |
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| Abstract: | A measure of local community structure was defined,and an mining algorithm of local community structure based on the minimal increment of link degree of a community was presented for resolving the time complexity problems of finding local community structure in complex networks.The algorithm ran in time O(kd) for general graphs,where d is the mean degree and k is the number of vertices to be explored.In order to determine its performance and calculation precision,the algorithm was compared with the classica... |
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| Keywords: | complex network link degree community structure mining algorithm |
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