PicHunter - The Porn Map
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nypd jst Target testing and the PicHunter Bayesian multimedia retrieval system Abstract: We address how the effectiveness of a content-based, multimedia information retrieval pichunter can be measured, and how such a system should best use response feedback in performing searches.
We propose a simple, quantifiable measure of an image retrieval system's effectiveness, "target testing", in which effectiveness is measured as the average number of images that a user must examine in searching for a given random target.
We describe an initial version of Pichunter, a retrieval system designed to test a novel approach to relevance-feedback. This approach is based on a Bayesian framework that incorporates an explicit model of the user's selection process.
PicHunter is intentionally designed to have a minimal, "queryless" user interface, so that its performance reflects only the performance of the relevance feedback algorithm. The algorithm, however, can easily be incorporated into more traditional, query-based systems.
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