Online adaptive filtering of messages

A non-transitory computer-usable medium storing a computer program for operating a spam filtering system in a messaging system that includes a message gateway and individual message boxes for users of the system, the computer program comprising instructions for causing at least one processor to:

• aggregate personal retraining data used to retrain personal, scoring e-mail classifiers that classify messages delivered to the individual message boxes as spam when a score for the messages exceeds a first threshold for classifying the messages as spam, wherein personal retraining data for an individual message box is based on a user's feedback about the classes of messages in the user's individual message box;
• determine a difference between a probability measure calculated for a message in the personal retraining data for the individual message box by a global, scoring e-mail classifier and a second threshold for classifying the messages as spam, the second threshold being higher than the first threshold;
• select a subset of the aggregated personal retraining data as global retraining data for retraining the global, scoring e-mail classifier that classifies messages received at a message gateway as spam when the difference exceeds a difference threshold;
• and
• retrain the global, scoring e-mail classifier based on the global retraining data so as to adjust which messages are classified as spam.

An apparatus for operating a spam filtering system in a messaging system that includes a message gateway and individual message boxes for users of the system, the apparatus comprising:

• a network interface configured to receive personal retraining data for an individual message box used to retrain personal, scoring e-mail classifiers that classify messages delivered to the individual message boxes as spam when a score for the messages exceeds a first threshold for classifying the messages as spam, wherein the personal retraining data is based on a user's feedback about the classes of messages in the user's individual message box over one or more network connections;
• and
• at least one processor configured by a set of instructions to (i) aggregate the received personal retraining data,
• (ii) determine a difference between a probability measure calculated for a message in the personal retraining data for the individual message box by a global, scoring e-mail classifier and a second threshold for classifying the messages as spam, the second threshold being higher than the first threshold,
• (iii) select a subset of the aggregated personal retraining data as global retraining data for retraining the global, scoring e-mail classifier that classifies messages received at a message gateway as spam when the difference exceeds a difference threshold, and
• (iii) retrain the global, scoring e-mail classifier based on the global retraining data so as to adjust which messages are classified as spam.