文章基本信息

标题：Enhanced K-mean Algorithm to Improve Decision Support System under Uncertain Situations
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作者：Ahmed Bahgat El Seddawy ; Turky Sultan ; Ayman Khedr 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2013
卷号：13
期号：7
页码：50-58
出版社：International Journal of Computer Science and Network Security
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 Investment Data Mining System (IDMS) will support top level management to make a good decision in any time under any uncertain environment and on another hand using enhancing K-mean algorithm.
关键词：dss; dm; mis; clustering; classification; association rule; k-mean; olap; matlab