Mail Filtering Algorithm Based on The Feedback Correction Probability Learning

DOI

10.2991/iccia.2012.443How to use a DOI?

Keywords

The feedback Probability learning, Spam, Probability

Abstract

With the popularity of the Internet, e-mail with its fast and convenient advantages has gradually developed into one of the important communication tools in people's lives. However, the problem of followed spam is increasingly severe, it is not only the dissemination of harmful information, but also waste of public resources. To solve this problem, the author proposed a mail filtering algorithm based on the feedback correction probability learning. The feedback correction probability training has less feedback learning data and use error-driven training in order to achieve a high classification effect. The experiment also tested the idea.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiao Yun Zou
AU  - Tao Wan
PY  - 2014/05
DA  - 2014/05
TI  - Mail Filtering Algorithm Based on The Feedback Correction Probability Learning
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1767
EP  - 1769
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.443
DO  - 10.2991/iccia.2012.443
ID  - Zou2014/05
ER  -