content-based tag generation to enable a tag-based collaborative tv-recommendation system.
With the application of the Web 2.0 philosophy to more and more online services and platforms, tagging has become a well established collaboration method. It is often used to simplify organization, navigation and discovery of information and resources in huge archives. In parallel, due to recent developments in digital television, audiences are confronted with a rising amount of available content and demand for better ways to discover programs of interest. In this paper, we propose a tagging-based solution to this problem. Using a content-based filtering approach, we present an individualized and flexible tag generation process. User specific as well as collaborative tag generation is enabled. Based on generated and user added tags, program recommendations are derived in a collaborative filtering step.
tag generation tags collaborative filtering metadata-based filtering folksonomy bayesian classifier tv recommender recommendation system epg