DocumentCode
3261807
Title
A Knowledge Management Platform for Optimization-based Data Mining
Author
Li, Xingsen ; Shi, Yong ; Liu, Ying ; Li, Jun ; Li, Aihua
Author_Institution
Sch. of Manage., Chinese Acad. of Sci., Beijing
fYear
2006
fDate
Dec. 2006
Firstpage
833
Lastpage
837
Abstract
Multiple criteria linear programming (MCLP) approach to data mining has been used in many fields. But users need to understand well with math and technology in its working process. This prevents it from wide applications. Studied on standards of data mining process and its advantages to project operation with the analysis on the characters of MCLP method and its process, we found the current data mining process model can not support MCLP in detail. So a knowledge management platform was presented for standardization the MCLP process by referring to CRISP-DM and the researches on data mining process models. The platform collects the experts´ experience in daily works of data mining and then accumulates knowledge for standardization. Its application in a Web company shows that it makes easier for different types of users to work in optimization-based data mining process
Keywords
data mining; knowledge management; linear programming; CRISP-DM; cross-industry standard process; data mining; knowledge management; multiple criteria linear programming; Acceleration; Australia; Customer relationship management; Data analysis; Data mining; Investments; Knowledge management; Linear programming; Risk management; Standardization;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2702-7
Type
conf
DOI
10.1109/ICDMW.2006.7
Filename
4063741
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