SmartMuseum : Personalized Context-aware Access to Digital Cultural Heritage

Abstract

This paper presents a semantic recommender method and a system for a personalized access to digital cultural heritage through context-aware user profiling. Given annotation knowledge-bases, explicit background knowledge in the form of ontologies, a user model capturing the user’s behavior and context, the system produces recommendations. Ontology-based user profiling can be used to reduce cold-start, sparsity and over-specialization problems. In addition, we present a recommendation retrieval method that is based on the vector space model and uses indices that enable fast and scalable implementation of the system.