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Titlebook: Adaptive Multimedia Retrieval: User, Context, and Feedback; Third International Marcin Detyniecki,Joemon M. Jose,C. J. Rijsbergen Conferen

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楼主: Optician
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Hiroshi Osano,Toshiaki Tachibanaki, the appearance of the extracted local features and their trajectories. At query-time, a probabilistic model of the visual pattern is estimated from the user interaction, captured through a relevance-feedback loop. We show that the method permits to efficiently retrieve video sequences that share, even partially, a spatio-temporal pattern.
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Paul J. J. Welfens,Holger C. Wolfe distribution of surface features in the TRECVID collection indicates that they are potentially useful, and a preliminary feedback experiment confirms that exploiting surface features can improve retrieval effectiveness.
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Paul J. J. Welfens,Holger C. Wolfof existing multimedia IR system performance evaluations. We propose a common framework in which to discuss the differing techniques proposed for relevance feedback and we develop a strategy for fairly comparing the relative performance of the techniques.
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The World Bank, Development, and Health, very suitable to find other images containing the same semantic object. The model combines fuzzy clustering and relevance feedback in the training stage, and uses fuzzy support vector machines in the generalization stage.
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Paul J. J. Welfens,Holger C. Wolf in encouraging the user to conceptualise their tasks and that it leads to increased user satisfaction. However, it could not be shown to increase performance. We identify the problems in the current setup, which when eliminated should lead to more effective searching overall.
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US Multinationals and Europe: An Updateoreover, the proposed approach is able to complement the role of relevance feedback by persistently maintaining the query parameters determined through user interaction over time and ensuring search efficiency. Experimental results on a database of about 10,000 images show the high quality contribution of the proposed approach.
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