Articles producció científica> Enginyeria Informàtica i Matemàtiques

Size reduction of complex networks preserving modularity

  • Identification data

    Identifier: imarina:5119271
    Authors:
    Arenas, ADuch, JFernandez, AGomez, S
    Abstract:
    The ubiquity of modular structure in real-world complex networks is 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 non-deterministic polynomial time hard (NP-hard) class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining their modularity. This size reduction allows use of 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. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.
  • Others:

    Author, as appears in the article.: Arenas, A; Duch, J; Fernandez, A; Gomez, S
    Department: Enginyeria Informàtica i Matemàtiques
    e-ISSN: 1367-2630
    URV's Author/s: Arenas Moreno, Alejandro / Duch Gavaldà, Jordi / Fernández Sabater, Alberto / Gómez Jiménez, Sergio
    Abstract: The ubiquity of modular structure in real-world complex networks is 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 non-deterministic polynomial time hard (NP-hard) class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining their modularity. This size reduction allows use of 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. © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.
    Thematic Areas: Química Psicología Physics, multidisciplinary Physics and astronomy (miscellaneous) Physics and astronomy (all) Medicina ii Materiais Matemática / probabilidade e estatística Interdisciplinar General physics and astronomy Ensino Engenharias iv Engenharias iii Engenharias i Ciências biológicas i Ciência da computação Biotecnología Astronomia / física
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: alberto.fernandez@urv.cat sergio.gomez@urv.cat jordi.duch@urv.cat alexandre.arenas@urv.cat
    Author identifier: 0000-0002-1241-1646 0000-0003-1820-0062 0000-0003-2639-6333 0000-0003-0937-0334
    Record's date: 2024-11-16
    Journal volume: 9
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://iopscience.iop.org/article/10.1088/1367-2630/9/6/176
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: New Journal Of Physics. 9 (6): PII S1367-2630(07)43446-2-176
    APA: Arenas, A; Duch, J; Fernandez, A; Gomez, S (2007). Size reduction of complex networks preserving modularity. New Journal Of Physics, 9(6), PII S1367-2630(07)43446-2-176. DOI: 10.1088/1367-2630/9/6/176
    Article's DOI: 10.1088/1367-2630/9/6/176
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2007
    Publication Type: Journal Publications
  • Keywords:

    Physics and Astronomy (Miscellaneous),Physics, Multidisciplinary
    Química
    Psicología
    Physics, multidisciplinary
    Physics and astronomy (miscellaneous)
    Physics and astronomy (all)
    Medicina ii
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    General physics and astronomy
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias i
    Ciências biológicas i
    Ciência da computação
    Biotecnología
    Astronomia / física
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