Modularity-Based Graph Clustering using Harmony Search Algorithm

Basit Öğe Kaydı
dc.contributor.authorAtay, Yilmaz
dc.contributor.authorKodaz, Halife
dc.date.accessioned2020-03-26T19:06:22Z
dc.date.available2020-03-26T19:06:22Z
dc.date.issued2015
dc.departmentSelçuk Üniversitesien_US
dc.description4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT) -- DEC 08-10, 2015 -- Kuala Lumpur, MALAYSIAen_US
dc.description.abstractReal-world networks contain variety of meaningful information inside them that can be revealed. These networks can be biological, social, ecological and technological networks. Each of these contains specific information about their field. This information cannot be obtained with simple techniques. Various techniques and algorithms have been developed to uncover useful information from complex relationships inside the network. In this paper, to divide graphs according to modularity measure to subgraphs harmony search algorithm is used which is inspired by music improvisation. This algorithm has been tested with 5 different real-world networks. The obtained quantitative values for each network have been given in the tables. In addition the proposed algorithm, has achieved the best known modularity measure of Zachary's Karate Club network which is commonly used in the literature and the latest subsets generated according to this modularity measure has been given at the end of section V. According to the results obtained from experiments it has been observed that HM algorithm gives faster results on solution of problem addressed in this study than most algorithms like genetic algorithm and bat algorithm. However, the proposed algorithm requires a larger size of harmony memory and more number of iterations for maximum modularity values.en_US
dc.description.sponsorshipDesign sci Renaissance, UNiTECH, PECAMP, MSTIen_US
dc.description.sponsorshipSelcuk University OYP Coordination [2013-OYP-057]; TUBITAK (The Scientific and Technological Research Council of Turkey, 2211-C Domestic Doctoral Scholarship Program Intended for Priority Areas) [1649B031402383]en_US
dc.description.sponsorshipThis study was supported by Selcuk University OYP Coordination (Project No. 2013-OYP-057) and TUBITAK (The Scientific and Technological Research Council of Turkey, 2211-C Domestic Doctoral Scholarship Program Intended for Priority Areas, No. 1649B031402383).en_US
dc.identifier.doi10.1109/ACSAT.2015.28en_US
dc.identifier.endpage114en_US
dc.identifier.isbn978-1-5090-0424-9
dc.identifier.issn2379-7738en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage109en_US
dc.identifier.urihttps://dx.doi.org/10.1109/ACSAT.2015.28
dc.identifier.urihttps://hdl.handle.net/20.500.12395/32332
dc.identifier.wosWOS:000454655600019en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2015 4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE APPLICATIONS AND TECHNOLOGIES (ACSAT)en_US
dc.relation.ispartofseriesInternational Conference on Advanced Computer Science Applications and Technologies
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectcommunity miningen_US
dc.subjectcomplex systemsen_US
dc.subjectgraph clusteringen_US
dc.subjectharmony search algorithmen_US
dc.subjectmodularityen_US
dc.subjectreal networksen_US
dc.titleModularity-Based Graph Clustering using Harmony Search Algorithmen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu