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.