Ontology-Based Collaborative Recommendation

Ahu Sieg, Bamshad Mobasher, Robin Burke
2010 User Modeling, Adaptation, and Personalization  
Recommender systems have emerged as critical tools that help alleviate the burden of information overload for users. Since these systems have to deal with a variety of modes of user interactions, collaborative recommendation must be sensitive to a user's specific context and changing interests over time. Our approach to building context-sensitive collaborative recommendation is a hybrid one that incorporates semantic knowledge in the form of a domain ontology. User profiles are defined relative
more » ... to the ontology, giving rise to an ontological user profile. In this paper, we describe how ontological user profiles are learned, incrementally updated, and used for collaborative recommendation. We empirically show that the ontological approach significantly improves the accuracy and coverage of recommendations.
dblp:conf/um/SiegMB10 fatcat:kurajypthrbxlct2xf7oihlmm4