Methodological and practical aspects of data mining

被引：81
|
作者：
Feelders, A
Daniels, H
Holsheimer, M
机构：
[1] Tilburg Univ, Dept Econ & Business Adm, NL-5000 LE Tilburg, Netherlands
[2] Rotterdam Sch Management, Inst Adv Management Studies, NL-3000 DR Rotterdam, Netherlands
[3] Data Distilleries, NL-1098 VA Amsterdam, Netherlands
来源：
INFORMATION & MANAGEMENT | 2000年 / 37卷 / 05期
关键词：
data mining; knowledge discovery in databases; data quality;
D O I：
10.1016/S0378-7206(99)00051-8
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We describe the different stages in the data mining process and discuss some pitfalls and guidelines to circumvent them. Despite the predominant attention on analysis, data selection and pre-processing are the most time-consuming activities, and have a substantial influence on ultimate success. Successful data mining projects require the involvement of expertise in data mining, company data, and the subject area concerned. Despite the attractive suggestion of 'fully automatic' data analysis, knowledge of the processes behind the data remains indispensable in avoiding the many pitfalls of data mining. (C) 2000 Elsevier Science B.V. All rights reserved.
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页码：271 / 281
页数：11
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