A self-organizing semantic map for information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Self-Organizing Maps
Information navigation on the web by clustering and summarizing query results
Information Processing and Management: an International Journal
Implementation and Analysis of Several Keyframe-Based Browsing Interfaces to Digital Video
ECDL '00 Proceedings of the 4th European Conference on Research and Advanced Technology for Digital Libraries
Self organization of a massive document collection
IEEE Transactions on Neural Networks
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Content-based video navigation is an efficient method for browsing video information. A common approach is to cluster shots into groups and visualize them afterwards. In this paper, we present a prototype that follows in general this approach. Unlike existing systems, the clustering is based on a growing self-organizing map algorithm. We focus on studying the applicability of SOMs for video navigation support. We ignore the temporal aspect completely during the clustering, but we project the grouped data on an original time bar control afterwards. This complements our interface by providing – at the same time – an integrated view of time and content based information. The aim is to supply the user with as much information as possible on one single screen, without overwhelming him. Special attention is also given to the interaction possibilities which are hierarchically organized.