Future trends in business analytics and optimization

被引：7

作者：

Brown, Donald E. ^{[2
]}

Famili, Fazel ^{[3
]}

Paass, Gerhard ^{[4
]}

Smith-Miles, Kate ^{[5
]}

Thomas, Lyn C. ^{[6
]}

Weber, Richard ^{[1
]}

Baeza-Yates, Ricardo ^{[7
]}

Bravo, Cristian ^{[1
]}

L'Huillier, Gaston ^{[8
]}

Maldonado, Sebastian ^{[9
]}

机构：

[1] Univ Chile, Dept Ind Engn, Santiago, Chile

[2] Univ Virginia, Dept Syst & Informat Engn, Charlottesville, VA USA

[3] Natl Res Council Canada, Ottawa, ON, Canada

[4] Fraunhofer IAIS, Aachen, Germany

[5] Monash Univ, Sch Math Sci, Clayton, Vic, Australia

[6] Univ Southampton, Sch Management, Southampton, Hants, England

[7] Yahoo Res, Barcelona, Spain

[8] Groupon Inc, Palo Alto, CA USA

[9] Univ Los Andes, Fac Engn & Appl Sci, Santiago, Chile

来源：

INTELLIGENT DATA ANALYSIS | 2011年 / 15卷 / 06期

关键词：

Future trends; Business Analytics and Optimization; Data Mining; Methodological Research; Real-life Applications;

D O I：

10.3233/IDA-2011-0506

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

During the last decades, the disciplines of Data Mining and Operations Research have been working mostly independent of each other. However, the increasing complexity of today's applications in areas such as business, medicine, and science requires more and more interaction between both disciplines. On the one hand, several data mining algorithms are based on optimization methods. On the other hand, in several applications the pure Knowledge Discovery in Databases (KDD) process is not sufficient since it does not take explicitly into account the entire decision process. This report presents future trends in Business Analytics and Optimization discussed at the panel sessions during the workshop on Business Analytics and Optimization (BAO'2010).

引用

页码：1001 / 1017

页数：17

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