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Published in:
2015 | OriginalPaper | Chapter
5. The Improved Bayesian Algorithm to Spam Filtering
Authors : Hongling Wang, Gang Zheng, Yueshun He
Published in: Proceedings of the 4th International Conference on Computer Engineering and Networks
Publisher: Springer International Publishing
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Abstract
Though electronic mail is one of the most popular forms of communication in modern society, spam brings considerable inconvenience to our lives while also very negatively affecting network security; thus resolving this issue has become a rather urgent task. The existing Bayesian algorithm uses a Bernoulli model to process text features in application to spam filtering, but it always misjudges normal mail because it does not distinguish the differing degrees of importance of various features. In this paper, a new and improved Bayesian algorithm is proposed that weights feature words with minimum risk. Experimental results show that this algorithm can reduce the risk of misjudging normal mail and improve the accuracy of mail filtering.