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Unbiased S-D Threshold Optimization, Initial Query Degradation, Decay, and Incrementality, for Adaptive Document Filtering

By Avi Arampatzis


We develop further the S-D threshold optimization method. Specifically, we deal with the bias problem introduced by receiving relevance judgements only for documents retrieved. The new approach estimates the parameters of the exponential-Gaussian score density model without using any relevance judgements. The standard expectation maximization (EM) method for resolving mixtures of distributions is used. In order to limit the number of documents that need to be buffered, we apply nonuniform document sampling , emphasizing the right tail (high scores) of the total score distribution

Year: 2001
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