ONTOTV: AN ONTOLOGY-BASED SYSTEM FOR THE MANAGEMENT OF INFORMATION ABOUT TELEVISION CONTENTS

Nowadays, there are a huge number of digital television platforms and channels, so it is not easy for the viewer to decide what they want to watch. Some television providers offer information about the programs they broadcast, but this information is usually scarce and there is no possibility to perform advanced operations like recommendation ones. For this reason, viewers could benefit from a system that integrates all the available information about contents, and applies semantics methodologies in order to provide a better television watching experience. The main objective of this research is the design of a television content management system, called OntoTV, which retrieves television content information from various existing sources and represents all these data in the best way possible by using knowledge engineering and ontologies. These semantic computing techniques make it possible to offer the viewers more useful operations on the stored data than traditional systems do, and with a high degree of personalization. Additionally, OntoTV accomplishes all of this regardless of the TV platform installed and the client device used. The viewers' satisfaction when using this system has been also studied to prove its functionality.