Actions for Size reduction of complex networks preserving modularity [electronic resource].

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Size reduction of complex networks preserving modularity [electronic resource].

Published
Berkeley, Calif. : Lawrence Berkeley National Laboratory, 2008.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Additional Creators
Lawrence Berkeley National Laboratory and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.
Report Numbers
E 1.99:lbnl-1444e
lbnl-1444e
Other Subject(s)
Note
Published through SciTech Connect.
12/24/2008.
"lbnl-1444e"
New Journal of Physics FT
Fernandez, A.; Arenas, A.; Gomez, S.; Duch, J.
Computational Research Division
Funding Information
DE-AC02-05CH11231
View MARC record | catkey: 14654139