A general approach for modules identification in evolving networks

Thang N. Dinh, Incheol Shin, Nhi K. Thai, My T. Thai, Taieb Znati

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Most complex networks exhibit a network modular property that is nodes within a network module are more densely connected among each other than with the rest of the network. Identifying network modules can help deeply understand the structures and functions of a network as well as design a robust system with minimum costs. Although there are several algorithms identifying the modules in literature, none can adaptively update modules in evolving networks without recomputing the modules from scratch. In this chapter, we introduce a general approach to efficiently detect and trace the evolution of modules in an evolving network. Our solution can identify the modules of each network snapshot based on the modules of previous snapshots, thus dynamically updating these modules. Moreover, we also provide a network compact representation which significantly reduces the size of the network, thereby minimizing the running time of any existing algorithm on the modules identification.

Original languageEnglish
Pages (from-to)83-100
Number of pages18
JournalSpringer Optimization and Its Applications
Volume40
DOIs
Publication statusPublished - 2010
Externally publishedYes

ASJC Scopus subject areas

  • Control and Optimization

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