An ontology-based personalized target advertisement system on interactive TV

We design and implement a personalized target advertisement (PTA) system in IPTV using ontology-based semantic relations between IPTV program and advertisement. In the PTA system, we focus on the development of an ontology reasoning technique of improving advertisement recommendation ability and exploiting efficient information reuse. For this purpose, we first build the IPTV program ontology and viewer profiling ontology based on the IPTV program and viewers’ content consumption behavior, using OWL (Web Ontology Language) standardized by W3C. We then classify each viewer into his/her corresponding reference group using a similarity metric. After that, we define the semantic relations between advertisement and shopping products consumed by the prototype through shopping sites in IPTV. Based on these semantic relations, we infer the preferred advertisements for each viewer through our reasoning process. In the experimental section, we demonstrate a prototype of our system and the algorithm of the PTA system using various cases.