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dc.contributor.authorLehnerer, Simon
dc.contributor.editorBecker, Michael
dc.date.accessioned2019-10-14T11:50:22Z
dc.date.available2019-10-14T11:50:22Z
dc.date.issued2018
dc.identifier.isbn978-3-88579-448-6
dc.identifier.issn1614-3213
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/28981
dc.description.abstractDetecting the community structure is of great interest when analyzing the topology of a network, however it is not a trivial problem. In this article a genetic algorithm is proposed which Ąnds the community structure of a network based on the maximization of a quality function called modularity. Tests using several sample networks show that it reliably Ąnds the community structure. However it does not resolve sufficiently small communities as intuitively expected due to an effect known as resolution limit.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSKILL 2018 - Studierendenkonferenz Informatik
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Seminars, Volume S-14
dc.subjectcomplex networks
dc.subjectcommunity detection
dc.subjectgenetic algorithm
dc.titleCommunity Detection in Complex Networks using Genetic Algorithmsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages35-46
mci.conference.sessiontitleInformatik Grundlagen
mci.conference.locationBerlin
mci.conference.date26.-27. September 2018


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