Applying evolutionary algorithms to the problem of information filtering

This paper presents an intelligent information filtering system that learns from user feedback and behavior through evolutionary algorithms. By applying the learning abilities of a classifier system and genetic algorithms to the system, the following tasks can be performed: (1) reducing a user's information overload; (2) predicting the actions that the users are supposed to do; and (3) prioritizing electronic mail.