Detailed Information

Cited 0 time in webofscience Cited 5 time in scopus
Metadata Downloads

Identifying the social-balanced densest subgraph from signed social networks

Full metadata record
DC Field Value Language
dc.contributor.authorHao, Fei-
dc.contributor.authorPark, Doo-Soon-
dc.contributor.authorPei, Zheng-
dc.contributor.authorLee, HwaMin-
dc.contributor.authorJeong, Young-Sik-
dc.date.accessioned2021-08-11T17:25:41Z-
dc.date.available2021-08-11T17:25:41Z-
dc.date.issued2016-07-
dc.identifier.issn0920-8542-
dc.identifier.issn1573-0484-
dc.identifier.urihttps://scholarworks.bwise.kr/sch/handle/2021.sw.sch/8977-
dc.description.abstractIdentifying the dense subgraphs from large graphs is important and useful to various social media mining applications. Most of existing works focus on the densest subgraph problem in the unweighted and undirected represented social network which can maximize the average degree over all possible subgraphs. However, considering the frequent signed relationships occurred in real-life social network, this paper introduces the social-balanced densest subgraph problem in signed social network by incorporating the social balance theory. We obtain a novel problem formulation that is to identify the subset of vertices that can maximize the social-balanced density in signed social networks. Further, we propose an efficient approach for identifying the social-balanced densest subgraph based on formal concept analysis. The case study illustrates that our algorithm can efficiently identify the social-balanced densest subgraph for satisfying the specific application's requirements.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherKluwer Academic Publishers-
dc.titleIdentifying the social-balanced densest subgraph from signed social networks-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1007/s11227-015-1606-6-
dc.identifier.scopusid2-s2.0-84951954288-
dc.identifier.wosid000379086300022-
dc.identifier.bibliographicCitationJournal of Supercomputing, v.72, no.7, pp 2782 - 2795-
dc.citation.titleJournal of Supercomputing-
dc.citation.volume72-
dc.citation.number7-
dc.citation.startPage2782-
dc.citation.endPage2795-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Hardware & Architecture-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordAuthorDensest subgraph-
dc.subject.keywordAuthorSigned social network-
dc.subject.keywordAuthorFCA-
dc.subject.keywordAuthorSBDS-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > Department of Computer Software Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE