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arxiv: 1305.4760 · v1 · pith:TJONVCQFnew · submitted 2013-05-21 · 💻 cs.SI · cs.DS· physics.soc-ph· q-bio.QM

How modular structure can simplify tasks on networks

classification 💻 cs.SI cs.DSphysics.soc-phq-bio.QM
keywords numbernetworknetworksnodescoarseneddensepreprocessingregions
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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(2^n), 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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