引用本文: | 马健,刘峰,李红辉,等.采用PageRank和节点聚类系数的标签传播重叠社区发现算法[J].国防科技大学学报,2019,41(1):183-190.[点击复制] |
MA Jian,LIU Feng,LI Honghui,et al.Overlapping community detection algorithm by label propagation using PageRank and node clustering coefficients[J].Journal of National University of Defense Technology,2019,41(1):183-190[点击复制] |
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采用PageRank和节点聚类系数的标签传播重叠社区发现算法 |
马健, 刘峰, 李红辉, 樊建平 |
(北京交通大学 计算机与信息技术学院, 北京 100044)
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摘要: |
基于标签传播的社区发现算法可以检测出复杂网络的重叠社区结构,因此提出了一种基于PageRank和节点聚类系数的重叠社区发现算法。该算法使用PageRank算法对节点的影响力进行排序,可以稳定社区发现结果,节点的聚类系数是一个与节点相关的值,使用节点聚类系数修改算法的参数并限制每个节点拥有最多标签的数量值,可以提高社区挖掘的质量。在人工网络和真实世界的网络上测试,实验验证了该算法能够有效地检测出重叠社区,并具有可接受的时间效率和算法复杂度。 |
关键词: 社区发现 重叠社区 标签传播 聚类系数 PageRank算法 节点影响力 |
DOI:10.11887/j.cn.201901025 |
投稿日期:2018-02-22 |
基金项目:国家863计划资助项目(2015AA043701) |
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Overlapping community detection algorithm by label propagation using PageRank and node clustering coefficients |
MA Jian, LIU Feng, LI Honghui, FAN Jianping |
(School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China)
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Abstract: |
Considering the fact that the community detection algorithm based on label propagation can detect overlapping community structures of complex networks, an overlapping community detection algorithm COPRAPC (community overlap propagation algorithm based on PageRank and clustering coefficient) was proposed. The algorithm used PageRank algorithm to rank the influence of nodes, which can stabilize the community finding results. The parameter of node clustering coefficient was a node related parameter, which can be used to modify the parameters of the algorithm and limit the maximum number of labels each node, so as to improve the quality of community mining. Experiments on artificial networks and real-world networks show that the algorithm can effectively detect overlapping communities, and the algorithm has acceptable time efficiency and algorithm complexity. |
Keywords: community detection overlapping community label propagation clustering coefficient PageRank algorithm node influence |
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