A Generative Model for Filtering Thresholds
نویسندگان
چکیده
This paper presents a generative model of score distribution, focused on the case of information filtering, where sampling of training data is not random. Parameters of the model were estimated using the Maximum Likelihood Principle, conjugate priors, and conjugate gradient descent. Experiments on TREC8 and TREC9 Filtering Track datasets are reported. Our method obtained significant improvements compared to a baseline.
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تاریخ انتشار 2001