How modular structure can simplify tasks on networks: parameterizing graph optimization by fast local community detection - Archive ouverte HAL
Article Dans Une Revue Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences Année : 2014

How modular structure can simplify tasks on networks: parameterizing graph optimization by fast local community detection

Binh-Minh Bui-Xuan
Nick S. Jones
  • Fonction : Auteur

Résumé

By considering the task of finding the shortest walk through a Network, we find an algorithm for which the run time is not as O(2n), with n being the number of nodes, but instead scales with the number of nodes in a coarsened network. This coarsened network has a number of nodes related to the number of dense regions in the original graph. Since we exploit a form of local community detection as a preprocessing, this work gives support to the project of developing heuristic algorithms for detecting dense regions in networks: preprocessing of this kind can accelerate optimization tasks on networks. Our work also suggests a class of empirical conjectures for how structural features of efficient networked systems might scale with system size.
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Dates et versions

hal-01146176 , version 1 (27-04-2015)

Identifiants

  • HAL Id : hal-01146176 , version 1

Citer

Binh-Minh Bui-Xuan, Nick S. Jones. How modular structure can simplify tasks on networks: parameterizing graph optimization by fast local community detection. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2014, 470 (2170), pp.20140224. ⟨hal-01146176⟩
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