Integrating E-Commerce and Data Mining: Architecture and Challenges

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. Note: A long version of this paper is also available [1].

• Type: Journal
• Year: 2000
• Where: CORR
• Authors: Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng
• Keywords: CORR 2000, Data Transformation Bridges, Data Understanding Effort, Education, Successful Data Mining