A major problem in using current best‐match methods in a filtering task is that of setting appropriate thresholds, which are required in order to force a binary decision on notifying a user of a document. We discuss methods for setting such thresholds and adapting them as a result of feedback information on the performance of the profile. These methods fit within the probabilistic approach to retrieval, and are applied to a probabilistic system. Some experiments, within the framework of the TREC‐7 adaptive filtering track, are described.
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