| dc.contributor.author | Aghdaie, Mohammad Hasan | |
| dc.contributor.author | Hashemkhani Zolfani, Sarfaraz | |
| dc.contributor.author | Zavadskas, Edmundas Kazimieras | |
| dc.date.accessioned | 2023-09-18T20:09:34Z | |
| dc.date.available | 2023-09-18T20:09:34Z | |
| dc.date.issued | 2014 | |
| dc.identifier.other | (BIS)VGT02-000029437 | |
| dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/147355 | |
| dc.description.abstract | Data 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.format | PDF | |
| dc.format.extent | p. 767-776 | |
| dc.format.medium | tekstas / txt | |
| dc.language.iso | eng | |
| dc.relation.ispartofseries | Procedia - social and behavioral sciences vol. 110 1877-0428 | |
| dc.relation.isreferencedby | Conference Proceedings Citation Index - Science (Web of Science) | |
| dc.relation.isreferencedby | ScienceDirect | |
| dc.source.uri | https://doi.org/10.1016/j.sbspro.2013.12.921 | |
| dc.source.uri | http://www.sciencedirect.com/science/article/pii/S1877042813055614 | |
| dc.subject | VE03 - Inovacijų vadyba / Innovation management | |
| dc.title | Synergies of data mining and multiple attribute decision making | |
| dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
| dcterms.references | 22 | |
| dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB | |
| dc.contributor.institution | Shomal University, Amol, Iran | |
| dc.contributor.institution | Amirkabir University of Technology, Tehran | |
| dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
| dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
| dc.subject.researchfield | S 003 - Vadyba / Management | |
| dc.subject.ltspecializations | L103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society | |
| dc.subject.en | Data Mining | |
| dc.subject.en | Multiple Attribute Decision Making (MADM) | |
| dc.subject.en | clustering | |
| dc.subject.en | SWARA | |
| dc.subject.en | VIKOR | |
| dc.subject.en | supplier clustering and ranking | |
| dcterms.sourcetitle | The 2-dn International scientific conference „Contemporary issues in business, management and education 2013" | |
| dc.publisher.name | Elsevier | |
| dc.publisher.city | Amsterdam | |
| dc.identifier.doi | 000466711800079 | |
| dc.identifier.doi | 10.1016/j.sbspro.2013.12.921 | |
| dc.identifier.elaba | 4102679 | |