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  • 标题:Adapted Framework for Data Mining Technique to Improve Decision Support System in an Uncertain Situation
  • 本地全文:下载
  • 作者:Ahmed Bahgat El Seddawy ; Ayman Khedr ; Turky Sultan
  • 期刊名称:International Journal of Data Mining & Knowledge Management Process
  • 印刷版ISSN:2231-007X
  • 电子版ISSN:2230-9608
  • 出版年度:2012
  • 卷号:2
  • 期号:3
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Decision Support System (DSS) is equivalent synonym as management information systems (MIS). Most of imported data are being used in solutions like data mining (DM). Decision supporting systems include also decisions made upon individual data from external sources, management feeling, and various other data sources not included in business intelligence. Successfully supporting managerial decision-making is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. Data mining have emerged to meet this need. They serve as an integrated repository for internal and external data-intelligence critical to understanding and evaluating the business within its environmental context. With the addition of models, analytic tools, and user interfaces, they have the potential to provide actionable information that supports effective problem and opportunity identification, critical decision-making, and strategy formulation, implementation, and evaluation. The proposed system will support top level management to make a good decision in any time under any uncertain environment.
  • 关键词:DSS; DM; MIS; CLUSTERING; CLASSIFICATION; ASSOCIATION RULE; K-MEAN; OLAP; MATLAB
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