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Cited 8 time in webofscience Cited 11 time in scopus
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Iceberg Clique queries in large graphs

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dc.contributor.authorHao, Fei-
dc.contributor.authorPei, Zheng-
dc.contributor.authorPark, Doo-Soon-
dc.contributor.authorYang, Laurence T.-
dc.contributor.authorJeong, Young-Sik-
dc.contributor.authorPark, Jong-Hyuk-
dc.date.accessioned2024-08-08T04:31:28Z-
dc.date.available2024-08-08T04:31:28Z-
dc.date.issued2017-09-20-
dc.identifier.issn0925-2312-
dc.identifier.issn1872-8286-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/18003-
dc.description.abstractThis paper investigates the Iceberg Clique (IC) queries in a large graph, specially, given a user-specified threshold theta, an IC query reports the cliques where the number of vertices exceeds left perpendicular theta|V| right perpendicular. Toward this end, a practical IC query theorem is formally proposed and proved. With this proposed query theorem, a formal context and its corresponding iceberg concept lattice are first constructed from an input graph topology by Modified Adjacency Matrix; then, we prove that the IC queries problem is equivalent to finding the iceberg equiconcepts whose number of elements exceeds left perpendicular theta|V| right perpendicular. Theoretical analysis and experimental results demonstrate that the proposed query algorithm is feasible and efficient for finding the iceberg cliques from large graphs. (C) 2017 Published by Elsevier B.V.-
dc.format.extent10-
dc.language영어-
dc.language.isoENG-
dc.publisherELSEVIER-
dc.titleIceberg Clique queries in large graphs-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.neucom.2015.12.142-
dc.identifier.scopusid2-s2.0-85019657800-
dc.identifier.wosid000404198500011-
dc.identifier.bibliographicCitationNEUROCOMPUTING, v.256, pp 101 - 110-
dc.citation.titleNEUROCOMPUTING-
dc.citation.volume256-
dc.citation.startPage101-
dc.citation.endPage110-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordAuthorIceberg concept lattice-
dc.subject.keywordAuthorIceberg Clique-
dc.subject.keywordAuthorFormal context-
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