Abstract
E-mail classification is an effective method to manage, improve process efficiency and filter junk mail. The extraction of E-mail characteristic is the key problem of exactness classification. In order to make the classification has a more distinct division characteristic words, IDF (Inverse document frequency) is used to epurate further the characteristic. The procedure which users deal with E-mail is a natural half-supervised learning. By using this process, proposed algorithm corrects classification results, adjust classification rule to adapt the individuation requirement of user automatically. The evaluation experiments indicate the availability of proposed algorithm.
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