TV Program Search and Recommendation Based on TV and Viewer Ontologies

In this paper we propose a searching and recommendation method of TV program contents based on TV contents and viewers ontologies by performing TV program usage examination, ontology matching, and recommendation processes. Our scheme searches TV programs by computing the similarity between contents ontologies, filter the candidates with preferences of viewers, and return the list of top-N ranked program contents. From the experimental results, we know that our scheme yields about 80% of average precision for 53 documentary programs.