A Prior Distribution for Anti-spam Statistical Bayesian Model

被引：0

作者：

Begriche, Youcef

Labiod, Houda

机构：

来源：

2009 INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE SECURITY | 2009年

关键词：

Beta function; Gamma function; Beta density; Marginal density; Conditional density; Distribution attachment; Binomial law; Spam; Ham; Bayesian statistical model; Classification;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper deals with Bayesian models applied to anti-spam. In most anti-spam related researches, authors assume that the probability of spam message is equal to 0.5, which is unrealistic. This pushes us to define a prior and a posterior probability laws to enhance the spam detection and increase the reliability decision. This work differs from previous results using the Bayesian approach for the anti-spam issue, especially through refinement and enhancement of various probability laws.

引用

页码：177 / 181

页数：5