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dc.contributor.authorAghdaie, Mohammad Hasan
dc.contributor.authorHashemkhani Zolfani, Sarfaraz
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.date.accessioned2023-09-18T20:09:34Z
dc.date.available2023-09-18T20:09:34Z
dc.date.issued2014
dc.identifier.other(BIS)VGT02-000029437
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/147355
dc.description.abstractData Mining (DM) and Multiple Attribute Decision Making (MADM) are two fast growing trends in Operations Research (OR) /Management Science (MS). In this article, we identify the synergies of data mining and MADM. Synergies can be attained by integration of MADM techniques into data mining and vice versa. The primary goal of the paper is to show a wide range of interactions between these two fields from a new perspective with an example of the integrated approach in supplier clustering and ranking. The integrated approach includes cluster analysis as a data mining tool and Step-wise Weight Assessment Ratio Analysis (SWARA) and VIseKriterijumskao ptimizacija i KOmpromisno Resenje (VIKOR) as the two MADM tools. More precisely, the features for clustering were selected and weighted by SWARA method and suppliers are clustered using two-stage cluster analysis. In addition, VIKOR technique is used to rank the clusters from the best to the worst one. The proposed integrated approach is presented to demonstrate the applicability of the proposed methodology.eng
dc.formatPDF
dc.format.extentp. 767-776
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.ispartofseriesProcedia - social and behavioral sciences vol. 110 1877-0428
dc.relation.isreferencedbyConference Proceedings Citation Index - Science (Web of Science)
dc.relation.isreferencedbyScienceDirect
dc.source.urihttps://doi.org/10.1016/j.sbspro.2013.12.921
dc.source.urihttp://www.sciencedirect.com/science/article/pii/S1877042813055614
dc.subjectVE03 - Inovacijų vadyba / Innovation management
dc.titleSynergies of data mining and multiple attribute decision making
dc.typeStraipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB
dcterms.references22
dc.type.pubtypeP1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB
dc.contributor.institutionShomal University, Amol, Iran
dc.contributor.institutionAmirkabir University of Technology, Tehran
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldS 003 - Vadyba / Management
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.enData Mining
dc.subject.enMultiple Attribute Decision Making (MADM)
dc.subject.enclustering
dc.subject.enSWARA
dc.subject.enVIKOR
dc.subject.ensupplier clustering and ranking
dcterms.sourcetitleThe 2-dn International scientific conference „Contemporary issues in business, management and education 2013"
dc.publisher.nameElsevier
dc.publisher.cityAmsterdam
dc.identifier.doi000466711800079
dc.identifier.doi10.1016/j.sbspro.2013.12.921
dc.identifier.elaba4102679


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