一种用于解析复杂网络中社区结构的信息论框架。
An information-theoretic framework for resolving community structure in complex networks.
作者信息
Rosvall Martin, Bergstrom Carl T
机构信息
Department of Biology, University of Washington, Seattle, WA 98195-1800, USA.
出版信息
Proc Natl Acad Sci U S A. 2007 May 1;104(18):7327-31. doi: 10.1073/pnas.0611034104. Epub 2007 Apr 23.
Abstract
To understand the structure of a large-scale biological, social, or technological network, it can be helpful to decompose the network into smaller subunits or modules. In this article, we develop an information-theoretic foundation for the concept of modularity in networks. We identify the modules of which the network is composed by finding an optimal compression of its topology, capitalizing on regularities in its structure. We explain the advantages of this approach and illustrate them by partitioning a number of real-world and model networks.
摘要
为了理解大规模生物、社会或技术网络的结构，将网络分解为更小的子单元或模块可能会有所帮助。在本文中，我们为网络模块化的概念建立了一个信息论基础。我们通过找到网络拓扑结构的最优压缩来识别其组成模块，利用结构中的规律。我们解释了这种方法的优点，并通过对一些真实世界和模型网络进行划分来说明这些优点。
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