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Abstract:
A data warehousing approach for recommender systems is proposed. We sketch an architecture for integrated OLAP and data mining in data waxehousing environments, and argue why this architecture can be extended for building recommender systems. Since producing recommendations can be considered as conceptual query answering, the relationship between conceptual query answering and intensional answers is also briefly examined.