A General Approach for Modules Identification in Evolving Networks

Thang N. Dinh (), Incheol Shin (), Nhi K. Thai (), My T. Thai () and Taieb Znati ()
Additional contact information
Thang N. Dinh: University of Florida
Incheol Shin: University of Florida
Nhi K. Thai: University of Minnesota
My T. Thai: University of Florida
Taieb Znati: University of Pittsburgh

Chapter Chapter 4 in Dynamics of Information Systems, 2010, pp 83-100 from Springer

Abstract: Summary 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.

Keywords: Network Module; Community Detection; Modular Structure; Evolve Network; Citation Network (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/978-1-4419-5689-7_4

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