Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/20088
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dc.contributor.authorPereira, L. R.-
dc.contributor.authorLouçã, J.-
dc.contributor.authorLopes, R. J.-
dc.date.accessioned2020-03-12T15:10:54Z-
dc.date.issued2020-
dc.identifier.issn2051-1310-
dc.identifier.urihttp://hdl.handle.net/10071/20088-
dc.description.abstractIn the last few years, the study of temporal networks has progressed markedly. The evolution of clusters of nodes (or communities) is one of the major focus of these studies. However, the time dimension increases complexity, introducing new constructs and requiring novel and enhanced algorithms. In spite of recent improvements, the relative scarcity of timestamped representations of empiric networks, with known ground truth, hinders algorithm validation. A few approaches have been proposed to generate synthetic temporal networks that conform to static topological specifications while in general adopting an ad hoc approach to temporal evolution. We believe there is still a need for a principled synthetic network generator that conforms to problem domain topological specifications from a static as well as temporal perspective. Here, we present such a system. The unique attributes of our system include accepting arbitrary node degree and cluster size distributions and temporal evolution under user control, while supporting tunable joint distribution and temporal correlation of node degrees. Theoretical contributions include the analysis of conditions for graphic sequences of inter- and intracluster node degrees and cluster sizes and the development of a heuristic to search for the cluster membership of nodes that minimizes the shared information distance between clusterings. Our work shows that this system is capable of generating networks under user controlled topology with up to thousands of nodes and hundreds of clusters with strong topology adherence. Much larger networks are possible with relaxed requirements. The generated networks support algorithm validation as well as problem domain analysis.eng
dc.language.isoeng-
dc.publisherOxford Academic Press-
dc.relationUID/EEA/50008/2013-
dc.relationUID/MULTI/0446/2013-
dc.rightsopenAccess-
dc.subjectGraph algorithmseng
dc.subjectNetwork flowseng
dc.subjectClusteringeng
dc.subjectTemporal networkseng
dc.subjectTopologyeng
dc.titleSyntgen: a system to generate temporal networks with user specified topologyeng
dc.typearticle-
dc.peerreviewedyes-
dc.journalJournal of Complex Networks-
dc.volume8-
dc.number14-
degois.publication.issue14-
degois.publication.titleSyntgen: a system to generate temporal networks with user specified topologyeng
dc.date.updated2020-11-24T14:29:42Z-
dc.description.versioninfo:eu-repo/semantics/acceptedVersion-
dc.identifier.doi10.1093/comnet/cnz039-
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Matemáticaspor
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.date.embargo2020-10-23-
iscte.subject.odsIndústria, inovação e infraestruturaspor
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-62714-
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IT-RI - Artigos em revistas científicas internacionais com arbitragem científica

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