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35

CIVR
2005
Springer

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Aspect-Based Relevance Learning for Image Retrieval

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Aspect-Based Relevance Learning for Image Retrieval

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We analyze the special structure of the relevance feedback learning problem, focusing particularly on the eﬀects of image selection by partial relevance on the clustering behavior of feedback examples. We propose a scheme, aspect-based relevance learning, which guarantees that feedback on feature values is accepted only once evidential support that the feedback was intended by the user is suﬃciently strong. The scheme additionally allows for natural simulation of the relevance feedback process. By means of simulation we analyze retrieval performance, search regularity and sensitivity to feature errors.

Mark J. Huiskes

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CIVR 2005 | Feedback Learning Problem | Relevance Feedback | Relevance Feedback Process |

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Added	26 Jun 2010
Updated	26 Jun 2010
Type	Conference
Year	2005
Where	CIVR
Authors	Mark J. Huiskes

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