Adaptive threshold based spam classification

Abstract

A spam classification manager uses a dynamically adaptive decision threshold for detecting spam email messages. For each of a plurality of time periods, the spam classification manager calculates an adaptive decision threshold to use to adjudicate whether or not received email messages comprise spam. The threshold is based on ratios between clean and spam emails received in previous time periods, as well as a misclassification cost ratio. The spam classification manager determines a likelihood of each incoming email message received during the time period being spam, and adjudicates whether each message in fact comprises spam by comparing the determined likelihood to the threshold. The spam classification manager keeps track of incoming email messages received during the time period adjudicated to be spam and adjudicated to be clean, and uses that information in the calculation of adaptive thresholds for future time periods.