Operations research and data mining

被引:133
|
作者
Olafsson, Sigurdur [1 ]
Li, Xiaonan [1 ]
Wu, Shuning [1 ]
机构
[1] Iowa State Univ, Dept Ind & Mfg Syst Engn, Ames, IA 50011 USA
关键词
data mining; optimization; classification; clustering; mathematical programming; heuristics;
D O I
10.1016/j.ejor.2006.09.023
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
With the rapid growth of databases in many modern enterprises data mining has become an increasingly important approach for data analysis. The operations research community has contributed significantly to this field, especially through the formulation and solution of numerous data mining problems as optimization problems, and several operations research applications can also be addressed using data mining methods. This paper provides a survey of the intersection of operations research and data mining. The primary goals of the paper are to illustrate the range of interactions between the two fields, present some detailed examples of important research work, and provide comprehensive references to other important work in the area. The paper thus looks at both the different optimization methods that can be used for data mining, as well as the data mining process itself and how operations research methods can be used in almost every step of this process. Promising directions for future research are also identified throughout the paper. Finally, the paper looks at some applications related to the area of management of electronic services, namely customer relationship management and personalization. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1429 / 1448
页数:20
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