【作者】 解；

【导师】 汪小帆；

【作者基本信息】 上海交通大学 ， 控制理论与控制工程， 2007， 硕士

【摘要】 社团结构是许多实际复杂网络的一个重要特征。寻找和分析社团有助于更好地了解网络的结构。人们提出了很多算法寻找网络的社团结构。早期的算法基于全局的信息寻找整个网络的社团结构,很难应用于大规模的网络。因此,寻找网络的局部社团结构开始逐渐受到关注。对具有社团结构的复杂网络建模有利于分析社团结构对网络性质和动态特性的影响。但是,当前大部分模型都建立在无权网络的基础上,并且不能很好的说明网络在社团层次上的幂律特性。因此,构建社团幂律分布的加权网络模型具有非常重要的现实意义。本文介绍了社团结构的基本概念,回顾了目前关于网络社团结构分析和建模的成果。论文的主要贡献如下:1基于社团规模和节点度的优先机制,提出了一种新的具有社团结构的网络演化模型。利用该模型生成的网络,社团规模的累积分布和节点的度分布都满足幂律特性,指数分别为ν≥1以及γ∈[2, +∞)。并且,这些网络还具有非常明显的等级结构,涵盖了从异配网络到同配网络的范围。2基于社团规模优先机制和节点权重优先机制,提出了一种新的具有社团结构的加权网络演化模型。该模型生成的网络社更多还原

【Abstract】 Community structure is an important characteristic in real complex networks. Seeking and analyzing communities is an invaluable tool of understanding the structure of networks. A lot of algorithms have been proposed to detect the community structure in networks. Based on the global information, early proposed algorithms detected the community structure of the whole network, which is problematic for large-scale networks. Thus, the algorithms for detecting local communities are under consideration.Modeling complex networks with communities helps us analyze the effects of community structure on network properties and dynamics. However, most of the proposed models are contributed to study unweighted networks and also fail to explain the scaling property of networks in the community level. Thus it is of great importance to build models with power-law distributed communities for weighted networks.In this thesis, we introduce the basic concepts of communities, and review the history research developments on analysis and modeling for community-structured networks. The contributions of this thesis are as更多还原