Titlebook: Community Structure of Complex Networks; Hua-Wei Shen Book 2013 Springer-Verlag Berlin Heidelberg 2013 Community structure.Complex Network

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书目名称Community Structure of Complex Networks影响因子(影响力)




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书目名称Community Structure of Complex Networks被引频次学科排名




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书目名称Community Structure of Complex Networks年度引用学科排名




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书目名称Community Structure of Complex Networks读者反馈学科排名

载货清单

Detecting the Overlapping and Hierarchical Community Structure in Networks,icipate in more than one community simultaneously and community further contains sub-communities. However, few methods are capable of simultaneously detecting the overlapping and hierarchical community structure in networks. In this chapter, taking maximal cliques as building blocks of community, a

与野兽博斗者

Multiscale Community Detection in Networks with Heterogeneous Degree Distributions,tigate the community structure at a single topological scale. However, community structure of real world networks often exhibits multiple topological descriptions. Furthermore, the detection of multiscale community structure is heavily affected by the heterogeneous distribution of node degree. In th

ITCH

Community Structure and Diffusion Dynamics on Networks,us scientific fields. However, it is still an open question how the community structure is associated with the dynamics on complex networks. In this chapter, we study the community structure associated with network dynamics by investigating the diffusion process on networks. We find that the intrins

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Exploratory Analysis of the Structural Regularities in Networks,ers of each group have similar patterns of connections to other groups. Then, we leverage generative model to describe network structure. The structural regularities are then naturally obtained by statistical inference using expectation maximization algorithm. The most prominent strength of our mode

minion

minion

https://doi.org/10.1007/978-3-642-31821-4Community structure; Complex Networks; Modularity; Multi-scale; Network Dynamics

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烦忧

https://doi.org/10.1007/978-3-642-76165-2om various fields. In this chapter, we will briefly introduce the research progress about the detection of community structure in networks. These include community definition, community detection methods, community evolution, measurements for evaluation, and test datasets used in this monograph. We

cloture

Hillert Ibbeken,Ruprecht Schleyericipate in more than one community simultaneously and community further contains sub-communities. However, few methods are capable of simultaneously detecting the overlapping and hierarchical community structure in networks. In this chapter, taking maximal cliques as building blocks of community, a