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INTEGRATING DATA MINING AND DECISION SUPPORT THROUGH DATA MINING BASED DECISION SUPPORT SYSTEM

机译:通过基于数据挖掘的决策支持系统集成数据挖掘和决策支持

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摘要

The information overload caused by the massive influx of raw data has caused traditional data analysis to become insufficient. This caused a new interdisciplinary field of data mining to arise, encompassing both classical statistical, and modern machine learning tools to support the data analysis and knowledge discovery from databases. While data mining methods are powerful in dealing with large quantities of data, they are often difficult to master by business users to facilitate decision support. In this paper we introduce our approach to integration of decision support system with data mining methods. We discuss the role of data mining to facilitate decision support, the role of data mining in decision support systems, discuss underlying ideas and applied approaches and introduce a data mining decision support system called DMDSS (Data Mining Decision Support System). We present some obtained results and their beneficial use as expected by the business users.
机译:大量原始数据导致的信息过载导致传统数据分析变得不足。这引起了数据挖掘的一个新的跨学科领域,它涵盖了经典统计和现代机器学习工具,以支持数据分析和从数据库中发现知识。尽管数据挖掘方法在处理大量数据方面功能强大,但通常难以被业务用户掌握以促进决策支持。在本文中,我们介绍了将决策支持系统与数据挖掘方法集成的方法。我们讨论了数据挖掘在促进决策支持中的作用,数据挖掘在决策支持系统中的作用,讨论了基础思想和应用方法,并介绍了一种称为DMDSS(数据挖掘决策支持系统)的数据挖掘决策支持系统。我们介绍了一些获得的结果以及它们对商业用户所期望的有益用途。

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