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CVPR
1998
IEEE

An Optimized Interaction Strategy for Bayesian Relevance Feedback

9 years 11 months ago
An Optimized Interaction Strategy for Bayesian Relevance Feedback
A new algorithm and systematic evaluation is presented for searching a database via relevance feedback. It represents a new image display strategy for the PicHunter system [2, 1]. The algorithm takes feedback in the form of relative judgments ("item A is more relevant than item B") as opposed to the stronger assumption of categorical relevance judgments ("item A is relevant but item B is not"). It also exploits a learned probabilistic model of human behavior to make better use of the feedback it obtains. The algorithm can be viewed as an extension of indexing schemes like the ? -d tree to a stochastic setting, hence the name "stochastic-comparison search." In simulations, the amount of feedback required for the new algorithm scales like ???????? ? , where ? ? is the size of the database, while a simple query-by-exampleapproach scales like ? ? , where depends on the structure of the database. This theoretical advantage is reflected by experiments with re...
Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka
Added 12 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 1998
Where CVPR
Authors Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka, Peter N. Yianilos
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