Decomposition in data mining: An industrial case study

被引:74
作者
Kusiak, A [1 ]
机构
[1] Univ Iowa, Intelligent Syst Lab, Iowa City, IA 52242 USA
来源
IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING | 2000年 / 23卷 / 04期
关键词
data mining; decision making; decomposition; integrated circuit; quality engineering;
D O I
10.1109/6104.895081
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Data mining offers tools for discovery of relationships, patterns, and knowledge in large databases. The knowledge extraction process is computationally complex and therefore a subset of all data is normally considered for mining. In this paper, numerous methods for decomposition of data sets are discussed. Decomposition enhances the quality of knowledge extracted from large databases by simplification of the data mining task. The ideas presented are illustrated with examples and an industrial case study. In the case study reported in this paper, a data mining approach is applied to extract knowledge from a data set. The extracted knowledge is used for the prediction and prevention of manufacturing faults in wafers.
引用
收藏
页码:345 / 354
页数:9
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