Algorithms for clustering data
Algorithms for clustering data
Addressing the challenge of visual information access from digital image and video libraries
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Evaluating the implicit feedback models for adaptive video retrieval
Proceedings of the international workshop on Workshop on multimedia information retrieval
A faceted interface for multimedia search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
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In this paper we introduce a novel interactive video retrieval approach which uses sub-needs of an information need for querying and organising the search process. The underlying assumption of this approach is that the search effectiveness will be enhanced when employed for interactive video retrieval. We explore the performance bounds of a faceted system by using the simulated user evaluation methodology on TRECVID data sets and also on the logs of a prior user experiment with the system. We discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. The facets are simulated by the use of clustering the video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness.