Integrating e-commerce and data mining: Architecture and challenges

被引:21
|
作者
Ansari, S [1 ]
Kohavi, R [1 ]
Mason, L [1 ]
Zheng, ZJ [1 ]
机构
[1] Blue Martini Software, San Mateo, CA 94403 USA
关键词
D O I
10.1109/ICDM.2001.989497
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We show that the e-commerce domain can provide all the right ingredients for successful data mining. We describe an integrated architecture for supporting this integration. The architecture can dramatically reduce the pre-processing, cleaning, and data understanding effort often documented to take 80% of the time in knowledge discovery projects. We emphasize the need for data collection at the application server layer (not the web server) in order to support logging of data and metadata that is essential to the discovery process. We describe the data transformation bridges required from the transaction processing systems and customer event streams (e.g., clickstreams) to the data warehouse. We detail the mining workbench, which needs to provide multiple views of the data through reporting, data mining algorithms, visualization, and OLAP. We conclude with a set of challenges.
引用
收藏
页码:27 / 34
页数:8
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