文章基本信息

标题：Synergies of Data Mining and Multiple Attribute Decision Making
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作者：Mohammad Hasan Aghdaie ; Mohammad Hasan Aghdaie ; Sarfaraz Hashemkhani Zolfani 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2014
卷号：110
页码：767-776
DOI：10.1016/j.sbspro.2013.12.921
语种：English
出版社：Elsevier
摘要：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.
关键词：data mining;Multiple Attribute Decision Making (MADM);Clustering;SWARA ;VIKOR;Supplier clustering and ranking