Study Minimum Risk Spam Filter Algorithm Based on Cognition-learning

DOI

10.2991/iccia.2012.453How to use a DOI?

Keywords

Minimum Risk, Cognition-learning, Bayesian

Abstract

The thesis puts forward anti-spam model and deficiency on spam filter based on minimum risk, and of austerity algorithm and through the introduction of cognition learning. The experiment proves that the forward of the method increased the recognition percentage of the spams, especially solved the problems of the spam filter.

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  - Qingmei Lu
AU  - Hongmin Liu
PY  - 2014/05
DA  - 2014/05
TI  - Study Minimum Risk Spam Filter Algorithm Based on Cognition-learning
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1804
EP  - 1807
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.453
DO  - 10.2991/iccia.2012.453
ID  - Lu2014/05
ER  -