# GN算法的设计与源代码+网络社区发现算法分析与比较

GN算法的设计与源代码+网络社区发现算法分析与比较

The Research and Realization of Girvan-Newman Algorithm
Abstract:  In complex networks, nodes can be divided into several groups. The density of links in group is bigger than those between, which is defined as the community of complex networks. The research of community of complex network leads two aspects virtues. On the one hand, it enables us to better understand the community of real world, such as interpersonal networks, disease transmission area; on the other hand, the theory of community structure of complex networks theory can be applied to design the actual network with good characteristics. The basic concepts of community are introduced firstly, and then several community detection algorithms are introduced. Three community detection algorithms are analyzed and compared, such as Girvan-Newman(GN) algorithm, online community detection algorithm based on latent semantic, factions filter algorithm. At last GN algorithm is realized and testing.
Keywords: complex networks; community structure detection; GN algorithm; latent semantic; faction filter algorithm

Abstract i

1 绪论 1
1.1 研究的背景 2
1.2 国内外研究现状 2
1.3 论文的组织结构 3
1.4 课题的目的和意义 3
2 网络社区发现算法分析与比较 4
2.1 网络社区发现算法分析 4
2.1.1 Girvan-Newman算法 4
2.1.2 基于潜在语义的网络社区发现算法 5
2.1.3 派系过滤法 6
2.2 网络社区发现算法的比较 7
2.3 分析三种算法的弊端及改进 10
2.3.1 GN算法的弊端及改进 10
2.3.2 基于潜在语义算法改进 10
3 GN算法的实现 12
3.1 GN算法的数学概念 12
3.2 GN算法的详细设计 13
3.3 GN算法的程序实现 14
3.3.1 开发环境 14
3.3.2 程序详细设计 15
3.4 GN算法测试结果及分析 27
4 结论 31
4.1 总结 31
4.2 心得体会 31

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