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2019-06-26Zeitschriftenartikel DOI: 10.3390/a12070127
Guidelines for Experimental Algorithmics: A Case Study in Network Analysis
dc.contributor.authorAngriman, Eugenio
dc.contributor.authorvan der Grinten, Alexander
dc.contributor.authorvon Looz, Moritz
dc.contributor.authorMeyerhenke, Henning
dc.contributor.authorNöllenburg, Martin
dc.contributor.authorPredari, Maria
dc.contributor.authorTzovas, Charilaos
dc.date.accessioned2019-09-10T11:14:25Z
dc.date.available2019-09-10T11:14:25Z
dc.date.issued2019-06-26none
dc.date.updated2019-08-22T22:50:49Z
dc.identifier.urihttp://edoc.hu-berlin.de/18452/21259
dc.description.abstractThe field of network science is a highly interdisciplinary area; for the empirical analysis of network data, it draws algorithmic methodologies from several research fields. Hence, research procedures and descriptions of the technical results often differ, sometimes widely. In this paper we focus on methodologies for the experimental part of algorithm engineering for network analysis—an important ingredient for a research area with empirical focus. More precisely, we unify and adapt existing recommendations from different fields and propose universal guidelines—including statistical analyses—for the systematic evaluation of network analysis algorithms. This way, the behavior of newly proposed algorithms can be properly assessed and comparisons to existing solutions become meaningful. Moreover, as the main technical contribution, we provide SimexPal, a highly automated tool to perform and analyze experiments following our guidelines. To illustrate the merits of SimexPal and our guidelines, we apply them in a case study: we design, perform, visualize and evaluate experiments of a recent algorithm for approximating betweenness centrality, an important problem in network analysis. In summary, both our guidelines and SimexPal shall modernize and complement previous efforts in experimental algorithmics; they are not only useful for network analysis, but also in related contexts.eng
dc.description.sponsorshipDeutsche Forschungsgemeinschaft
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectexperimental algorithmicseng
dc.subjectnetwork analysiseng
dc.subjectapplied graph algorithmseng
dc.subjectstatistical analysis of algorithmseng
dc.subject.ddc510 Mathematiknone
dc.titleGuidelines for Experimental Algorithmics: A Case Study in Network Analysisnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/21259-0
dc.identifier.doi10.3390/a12070127none
dc.identifier.doihttp://dx.doi.org/10.18452/20500
dc.type.versionpublishedVersionnone
local.edoc.container-titleAlgorithmsnone
local.edoc.pages37none
local.edoc.type-nameZeitschriftenartikel
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameMDPInone
local.edoc.container-publisher-placeBaselnone
local.edoc.container-volume12none
local.edoc.container-issue7none
dc.description.versionPeer Reviewednone
dc.identifier.eissn1999-4893
local.edoc.affiliationAngriman, Eugenio; Department of Computer Science, Humboldt-Universität zu Berlin, 10099 Berlin, Germany,none
local.edoc.affiliationvan der Grinten, Alexander; Department of Computer Science, Humboldt-Universität zu Berlin, 10099 Berlin, Germany,none
local.edoc.affiliationvon Looz, Moritz; Department of Computer Science, Humboldt-Universität zu Berlin, 10099 Berlin, Germany,none
local.edoc.affiliationMeyerhenke, Henning; Department of Computer Science, Humboldt-Universität zu Berlin, 10099 Berlin, Germany,none
local.edoc.affiliationNöllenburg, Martin; Algorithms and Complexity Group, Institute of Logic and Computation, TU Wien, 1040 Vienna, Austria,none
local.edoc.affiliationPredari, Maria; Department of Computer Science, Humboldt-Universität zu Berlin, 10099 Berlin, Germany,none
local.edoc.affiliationTzovas, Charilaos; Department of Computer Science, Humboldt-Universität zu Berlin, 10099 Berlin, Germany,none

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