A television program recommendation system using semantic web

Semantic web technologies are of the most important technologies that are gaining popularity in academic and industrial society and expected to become widespread. By way of using semantic web technologies, the data on the web will not be just human readable documents, but it will be in a form that allows computers to understand the connections between data and find out new connections built upon existing ones by inference mechanisms.Television broadcasters can also employ semantic web technologies to provide new and highly personalized television experiences to their viewers and the whole world. Viewers could get personalized TV program recommendations or commercial advertisements via web clients, thin clients or clients that run directly on TV screen.In this thesis, a web client software is developed for retrieving The Turkish Radio and Television Broadcasting Institution's (TRT) television broadcast listing semantically on the web and provide personalized recommendations to viewers.