GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Tailoring the interaction with users in electronic shops
UM '99 Proceedings of the seventh international conference on User modeling
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Knowledge-Based Systems for Engineers and Scientists
Knowledge-Based Systems for Engineers and Scientists
International Journal of Electronic Commerce
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The concept of personalization has long been advocated to be one of the edges to improve the stickiness of on-line stores. By enabling an on-line store with adequate knowledge about the preference characteristics of different customers, it is possible to provide customized services to further raise the customer satisfaction level. In this paper, we describe in detail how to implement a knowledge-based recommender system for supporting such an adaptive store. Our proposed conceptual framework is characterized by a user profiling and product characterization module, a matching engine, an intelligent gift finder, and a backend subsystem for content management. A prototype of an on-line furnishing company has been built for idea illustration. Limitations and future extensions of the proposed system are also discussed.