Multi-Media Fusion Through Application of Machine Learning and NLP

Machine Learning in Information Access

Volume

Papers from the 1996 AAAI Spring Symposium

Contents

This paper describes work on a system to dynamically cluster and present information from live multimedia news sources. Features are obtained by applying statistical and natural language processing techniques to texts associated with the media (new wire stories or closed-captions). Conceptual clustering is employed to dynamically build a set of hierarchical clusters. Results are presented objectively comparing automated clustering with hand clustering of the same articles.