A user meta-model for context-aware recommender systems

Authors:
Jon Imanol Durán;Juhani Laitakari;Daniel Pakkala;Juho Perälä
Affiliations:
VTT Research Centre of Finland, Oulu, Finland;VTT Research Centre of Finland, Oulu, Finland;VTT Research Centre of Finland, Oulu, Finland;VTT Research Centre of Finland, Oulu, Finland
Venue:
Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Year:
2010

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Abstract

User profiles are increasingly used for sharing standard information about users among context-aware agents. User profiles allow agents to offer users personalized content and services. However, the entities and contextual information used by these agents must have same meaning in order to share a common understanding about user related personal information, context and preferences. The contribution of this paper is to present a general user metadata model which is integrated within a generic metadata model (CAM Meta-model) that covers altogether information about content, services, physical and technical environment. This new user profile meta-model has been designed with a view of using it in conjunction with content and service recommender systems. It brings new opportunities to reason over user context data with the main purpose of increasing user experience in ubiquitous environments and satisfying their desires depending on the circumstances.