Spam Filtering: the Influence of the Temporal Distribution of Training Data

Authors:
Anton Bryl
Affiliations:
University of Trento, Italy/ Create-Net, Italy
Venue:
Proceedings of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium
Year:
2006

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Abstract

The great number and variety of learning-based spam filters proposed during the last years cause the need in many-sided evaluation of them. This paper is dedicated to the evaluation of the dependence of filtering accuracy on the temporal distribution of training data. Such evaluation may be useful for organizing effective training of the filter.