Detecting overlapping communities in networks via dominant label propagation

被引:1
|
作者
孙鹤立 [1 ,2 ]
黄健斌 [2 ,3 ]
田勇强 [3 ]
宋擒豹 [1 ]
刘怀亮 [4 ]
机构
[1] Department of Computer Science and Technology, Xi’an Jiaotong University
[2] State Key Laboratory for Novel Software Technology, Nanjing University
[3] School of Software, Xidian University
[4] School of Economics and Management, Xidian University
基金
中央高校基本科研业务费专项资金资助; 中国国家自然科学基金;
关键词
overlapping community detection; dominant label propagation; complex network;
D O I
暂无
中图分类号
O157.5 [图论];
学科分类号
070104 ;
摘要
Community detection is an important methodology for understanding the intrinsic structure and function of a realworld network.In this paper,we propose an effective and efficient algorithm,called Dominant Label Propagation Algorithm(Abbreviated as DLPA),to detect communities in complex networks.The algorithm simulates a special voting process to detect overlapping and non-overlapping community structure in complex networks simultaneously.Our algorithm is very efficient,since its computational complexity is almost linear to the number of edges in the network.Experimental results on both real-world and synthetic networks show that our algorithm also possesses high accuracies on detecting community structure in networks.
引用
收藏
页码:555 / 563
页数:9
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