A Knowledge Management Platform for Optimization-based Data Mining
- Resource Type
- Conference
- Authors
- Xingsen Li; Yong Shi; Ying Liu; Jun Li; Aihua Li
- Source
- Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06) Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on. :833-837 Dec, 2006
- Subject
- Computing and Processing
Knowledge management
Data mining
Standardization
Linear programming
Acceleration
Customer relationship management
Risk management
Investments
Data analysis
Australia
- Language
- ISSN
- 2375-9232
2375-9259
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.