Hierarchical analysis for discovering knowledge in large databases

被引：0
|
作者：
Pai, WC [1 ]
机构：
[1] Soochow Univ, Dept Business Math, Taipei, Taiwan
来源：
INFORMATION SYSTEMS MANAGEMENT | 2003年 / 21卷 / 01期
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This article presents a goal-question-metric paradigm for selecting and implementing metrics for data mining, as well as a case study to illustrate that paradigm. The aim of this technique is to increase customer satisfaction and retention rate. It is especially useful for transaction records that are incomplete and therefore cannot be used as is for data mining. By analyzing the company's goal and strategies, data mining rules can be developed to discover associations within the available data.
引用
收藏
页码：81 / 88
页数：8
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