摘要
为使企业能有效地从不同角度观察其销售历史数据,以利于决策层做出分析决策,文中将在线分析和数据挖掘两者有机结合,利用属性的信息增益技术对其产品属性进行归纳泛化,泛化后对不同概念的数据进行分层处理,寻找数据依赖关系,在数据集中找出分类规则,建立一个可视化挖掘模型。最后用实验证明其提出的挖掘观察方法是可行和有效的。
In order to observe historical sales figures and make important decisions for enterprises, OLAP and data mining were combined to generalize attributes of products. After attribute generalization is used to process hierarchical ordering of data, the technology of information gain is used to find dependency relation of data and find classification rules, and establish a visualized data mining model. Moreover, practical applications proves the practicality of this method.
出处
《微型电脑应用》
2009年第1期54-55,50,共3页
Microcomputer Applications
关键词
数据挖掘
属性泛化
信息增益
OLAP
可视化
Data mining
Attribute generalization
Information gain
OLAP
Visualization
