Capturing interest through inference and visualization: ontological user profiling in recommender systems

Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a diverse and dynamic environment. Recommender systems help where explicit search queries are not available or are difficult to formulate, learning the type of thing users like over a period of time. We explore an ontological approach to user profiling in the context of a recommender system. Building on previous work involving ontological profile inference and the use of external ontologies to overcome the cold-start problem, we explore the idea of profile visualization to capture further knowledge about user interests. Our system, called Foxtrot, examines the problem of recommending on-line research papers to academic researchers. Both our ontological approach to user profiling and our visualization of user profiles are novel ideas to recommender systems. A year long experiment is conducted with over 200 staff and students at the University of Southampton. The e...

• Type: Conference
• Year: 2003
• Where: KCAP
• Authors: Stuart E. Middleton, Nigel R. Shadbolt, David De Roure
• Keywords: KCAP 2003, Ontological Approach, Recommender Systems, User