History-Based Email Prioritization

The rise of email as a communication medium raises several issues. A majority of email messages sent are spam. Also, the amount of legitimate email received by many users is overwhelming. In this paper, we propose two new methods of performing email prioritization. Both techniques rank users inboxes using models created from email history. With them, lower priority email messages may be dealt with so that the use of email remains a net productivity gain.