Context Boosting Collaborative Recommendations

Abstract

This paper describes the operation of and research behind a networked application for the delivery of personalised streams of music at Trinity College Dublin. Smart Radio is a web based client-server application that uses streaming audio technology and recommendation techniques to allow users build, manage and share music programmes. Since good content descriptors are difficult to obtain in the audio domain, we originally used automated collaborative filtering, a `content less? approach as our recommendation strategy. We describe how we improve the ACF technique by leveraging a light content-based technique that attempts to capture the user?s current listening `context?. This involves a two stage retrieval process where ACF recommendations are ranked according to the user?s current interests. Finally, we demonstrate a novel online evaluation strategy that pits the ACF strategy against the context-boosted strategy in a real time competition.