Ontology-based recommender system of TV programmes for personalisation service in smart TV
Jung Min Kim, Hee Deok Yang, Hyun-Sook Chung · International Journal of Web and Grid Services · 2015
Many researches endeavour to solve the problem of information overload and deliver the preferred TV programme content to users. However, they have a weakness in the similarity computation of TV programmes for recommendation because they do not consider the knowledge structures of TV programme content. In this paper, we propose a similarity matching and recommendation method for TV programme content to reduce information overload. Our approach is composed of the three major tasks: (1) conceptualisation and construction of TV programme domain ontologies, (2) computation of the similarity of programme content based on domain ontologies and (3) user preference-based filtering and semantic score-based ranking of the recommendation list. To support semantic-based TV content searching and recommendation, we first design the semantic model of TV ontology and a conceptual process to transform the textual content descriptions of TV programmes to semantic maps. Subjective experiments confirm that the proposed method is effective in semantic-based searching and recommendation.