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Cited 9 time in webofscience Cited 9 time in scopus
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dc.contributor.authorDress, A-
dc.contributor.authorHuber, K-
dc.contributor.authorKoolen, J-
dc.contributor.authorMoulton, V-
dc.contributor.authorSpillner, A-
dc.date.accessioned2016-04-01T02:40:34Z-
dc.date.available2016-04-01T02:40:34Z-
dc.date.created2010-11-24-
dc.date.issued2010-09-
dc.identifier.issn0176-4268-
dc.identifier.other2010-OAK-0000022019-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/25566-
dc.description.abstractThe theory of the tight span, a cell complex that can be associated to every metric D, offers a unifying view on existing approaches for analyzing distance data, in particular for decomposing a metric D into a sum of simpler metrics as well as for representing it by certain specific edge-weighted graphs, often referred to as realizations of D. Many of these approaches involve the explicit or implicit computation of the so-called cutpoints of (the tight span of) D, such as the algorithm for computing the "building blocks" of optimal realizations of D recently presented by A. Hertz and S. Varone. The main result of this paper is an algorithm for computing the set of these cutpoints for a metric D on a finite set with n elements in O(n3) time. As a direct consequence, this improves the run time of the aforementioned O(n6)-algorithm by Hertz and Varone by "three orders of magnitude".-
dc.description.statementofresponsibilityX-
dc.languageEnglish-
dc.publisherSPRINGER-
dc.relation.isPartOfJOURNAL OF CLASSIFICATION-
dc.subjectMetric-
dc.subjectCutpoint-
dc.subjectRealization-
dc.subjectTight span-
dc.subjectDecomposition-
dc.subjectBlock-
dc.subjectBLOCK REALIZATIONS-
dc.subjectPARTITION PROBLEM-
dc.subjectCUT POINTS-
dc.titleAn Algorithm for Computing Cutpoints in Finite Metric Spaces-
dc.typeArticle-
dc.contributor.college수학과-
dc.identifier.doi10.1007/S00357-010-9055-7-
dc.author.googleDress, A-
dc.author.googleHuber, K-
dc.author.googleKoolen, J-
dc.author.googleMoulton, V-
dc.author.googleSpillner, A-
dc.relation.volume27-
dc.relation.issue2-
dc.relation.startpage158-
dc.relation.lastpage172-
dc.contributor.id10200295-
dc.relation.journalJOURNAL OF CLASSIFICATION-
dc.relation.indexSCI급, SCOPUS 등재논문-
dc.relation.sciSCIE-
dc.collections.nameJournal Papers-
dc.type.rimsART-
dc.identifier.bibliographicCitationJOURNAL OF CLASSIFICATION, v.27, no.2, pp.158 - 172-
dc.identifier.wosid000282102500003-
dc.date.tcdate2019-02-01-
dc.citation.endPage172-
dc.citation.number2-
dc.citation.startPage158-
dc.citation.titleJOURNAL OF CLASSIFICATION-
dc.citation.volume27-
dc.contributor.affiliatedAuthorKoolen, J-
dc.identifier.scopusid2-s2.0-77957146041-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc6-
dc.description.scptc6*
dc.date.scptcdate2018-05-121*
dc.type.docTypeArticle-
dc.subject.keywordAuthorMetric-
dc.subject.keywordAuthorCutpoint-
dc.subject.keywordAuthorRealization-
dc.subject.keywordAuthorTight span-
dc.subject.keywordAuthorDecomposition-
dc.subject.keywordAuthorBlock-
dc.relation.journalWebOfScienceCategoryMathematics, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryPsychology, Mathematical-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassahci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalResearchAreaPsychology-

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