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.