Title :
Spam filtering system based on rough set and Bayesian classifier
Author :
Wang, Yun ; Wu, Zhiqiang ; Wu, Runxiu
Author_Institution :
Comput. Dept., NanChang Inst. of Technol., Nanchang
Abstract :
Proposed in this paper is a spam filtering method based on rough set theory and Bayesian classifier algorithm. First, mutual dependence model is used to extract the features of email content. Then the amount of features are reduced by deleting redundant features with little significance on filtering effect based on rough set theory, result in a input sample with reduced number of dimension. Experiments proved that this mechanism could greatly boost both the systempsilas accuracy and efficiency.
Keywords :
Bayes methods; e-mail filters; pattern classification; rough set theory; unsolicited e-mail; Bayesian classifier algorithm; email content; mutual dependence model; rough set theory; spam filtering system; Bayesian methods; Data mining; Feature extraction; Filtering algorithms; Filtering theory; Information filtering; Information filters; Probability; Set theory; Unsolicited electronic mail; Email; Mutual dependence; Naive Bayesian; Rough set; classifier;
Conference_Titel :
Granular Computing, 2008. GrC 2008. IEEE International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-2512-9
Electronic_ISBN :
978-1-4244-2513-6
DOI :
10.1109/GRC.2008.4664716
