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.
Integrating e-commerce and data mining: architecture and challenges
S. Ansari,Ron Kohavi,Llew Mason,Zijian Zheng
Published 2000 in Proceedings 2001 IEEE International Conference on Data Mining
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- Publication year
2000
- Venue
Proceedings 2001 IEEE International Conference on Data Mining
- Publication date
2000-07-13
- Fields of study
Business, Computer Science
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