Topic labeling of broadcast news stones in the Informedia Digital Video Library

Abstract

This paper describes the implementation of a topic labeling component for the Informedia Digital Video Library. Each news story recorded from the evening news is assigned to one of 3178 topic categories using a K-nearest neighbor classification algorithm. In preliminary tests, the system achieved recall of 0.491 with relevance of 0.482 when up to 5 topics could be assigned to a news story.