Communications of the ACM
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
User Modeling and User-Adapted Interaction
Information Filtering: Overview of Issues, Research and Systems
User Modeling and User-Adapted Interaction
Collaborative Case-Based Recommender Systems
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
ITR: A Case-Based Travel Advisory System
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Ubiquitous user modeling in recommender systems
UM'05 Proceedings of the 10th international conference on User Modeling
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The growth of available entertainment information services, such as movies and CD listings, or travels and recreational activities, raises a need for personalization techniques for filtering and adapting contents to customer's interest and needs. Personalization technologies rely on users data, represented as User Models (UMs). UMs built by specific services are usually not transferable due to commercial competition and models' representation heterogeneity. This paper focuses on the second obstacle and discusses architecture for mediating UMs across different domains of entertainment. The mediation facilitates improving the accuracy of the UMs and upgrading the provided personalization.