Community detection in complex networks by dynamical simplex evolution

V. Gudkov; V. Montealegre; S. Nussinov; Z. Nussinov

doi:10.1103/PhysRevE.78.016113

Community detection in complex networks by dynamical simplex evolution

V. Gudkov
, V. Montealegre
, S. Nussinov
, Z. Nussinov

Department of Physics

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

We benchmark the dynamical simplex evolution (DSE) method with several of the currently available algorithms to detect communities in complex networks by comparing correctly identified nodes for different levels of "fuzziness" of random networks composed of well-defined communities. The potential benefits of the DSE method to detect hierarchical substructures in complex networks are discussed.

Original language	English
Article number	016113
Journal	Physical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume	78
Issue number	1
DOIs	https://doi.org/10.1103/PhysRevE.78.016113
State	Published - Jul 23 2008

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title = "Community detection in complex networks by dynamical simplex evolution",

abstract = "We benchmark the dynamical simplex evolution (DSE) method with several of the currently available algorithms to detect communities in complex networks by comparing correctly identified nodes for different levels of {"}fuzziness{"} of random networks composed of well-defined communities. The potential benefits of the DSE method to detect hierarchical substructures in complex networks are discussed.",

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AU - Gudkov, V.

AU - Montealegre, V.

AU - Nussinov, S.

AU - Nussinov, Z.

PY - 2008/7/23

Y1 - 2008/7/23

N2 - We benchmark the dynamical simplex evolution (DSE) method with several of the currently available algorithms to detect communities in complex networks by comparing correctly identified nodes for different levels of "fuzziness" of random networks composed of well-defined communities. The potential benefits of the DSE method to detect hierarchical substructures in complex networks are discussed.

AB - We benchmark the dynamical simplex evolution (DSE) method with several of the currently available algorithms to detect communities in complex networks by comparing correctly identified nodes for different levels of "fuzziness" of random networks composed of well-defined communities. The potential benefits of the DSE method to detect hierarchical substructures in complex networks are discussed.

UR - https://www.scopus.com/pages/publications/48349122191

U2 - 10.1103/PhysRevE.78.016113

DO - 10.1103/PhysRevE.78.016113

M3 - Article

AN - SCOPUS:48349122191

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JO - Physical Review E - Statistical, Nonlinear, and Soft Matter Physics

JF - Physical Review E - Statistical, Nonlinear, and Soft Matter Physics

IS - 1

M1 - 016113

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Community detection in complex networks by dynamical simplex evolution

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