DC FieldValueLanguage
dc.contributor.authorJovanović, Đorđeen_US
dc.contributor.authorDavidović, Tatjanaen_US
dc.contributor.authorUrošević, Draganen_US
dc.contributor.authorJakšić Kruger, Tatjanaen_US
dc.contributor.authorRamljak, Dušanen_US
dc.date.accessioned2023-06-27T08:58:21Z-
dc.date.available2023-06-27T08:58:21Z-
dc.date.issued2023-01-01-
dc.identifier.isbn978-3-031-32411-6-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/5096-
dc.description.abstractCommunity detection on graphs can help people gain insight into the network’s structural organization, and grasp the relationships between network nodes for various types of networks, such as transportation networks, biological networks, electric power networks, social networks, blockchain, etc. The community in the network refers to the subset of nodes that have greater similarity, i.e. have relatively close internal connections. They should also have obvious differences with members from different communities, i.e. relatively sparse external connections. Solving the community detection problem is one of long standing and challenging optimization tasks usually treated by metaheuristic methods. Thus, we address it by basic variable neighborhood search (BVNS) approach using modularity as the score for measuring quality of solutions. The conducted experimental evaluation on well-known benchmark examples revealed the best combination of BVNS parameters. Preliminary results of applying BVNS with thus obtained parameters are competitive in comparison to the state-of-the-art methods from the literature.en_US
dc.publisherSpringer Linken_US
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.subjectMetaheuristics | Modularity maximization | Optimization on graphs | Social networksen_US
dc.titleVariable Neighborhood Search Approach to Community Detection Problemen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference NMA 2022: Numerical Methods and Applicationsen_US
dc.identifier.doi10.1007/978-3-031-32412-3_17-
dc.identifier.scopus2-s2.0-85161113841-
dc.contributor.affiliationComputer Scienceen_US
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Artsen_US
dc.relation.firstpage188-
dc.relation.lastpage199-
dc.relation.volumeLNCS 13858-
dc.description.rankM33-
item.openairetypeConference Paper-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
crisitem.author.orcid0000-0003-1222-1292-
crisitem.author.orcid0000-0001-9561-5339-
crisitem.author.orcid0000-0003-3607-6704-
crisitem.author.orcid0000-0001-6766-4811-
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