An online system with end-user services: mining novelty concepts from tv broadcast subtitles

Mika Rautiainen, Jouni Sarvanko, Arto Heikkinen, Mika Ylianttila, Vassilis Kostakos

Abstract: Better tools for content-based access of video are needed to improve access to time-continuous video data. Particularly information about linear TV broadcast programs has been available in a form limited to program guides that provide short manually described overviews of the program content. Recent development in digitalization of TV broadcasting and emergence of web-based services for catch-up and on-demand viewing bring out new possibilities to access data. In this paper we introduce our data mining system and accompanying services for summarizing Finnish DVB broadcast streams from seven national channels. We describe how data mining of novelty concepts can be extracted from DVB subtitles to augment web-based "Catch-Up TV Guide" and "Novelty Cloud" TV services. Furthermore, our system allows accessing media fragments as Picture Quotes via generated word lists and provides content-based recommendations to find new programs that have content similar to the user selected programs. Our index consists of over 180 000 programs that are used to recommend relevant programs. The service has been under development and available online since 2010. It has registered over 5000 user sessions.