Title :
Research on illegal E-mails recognition Based on Bayesian Formula and Statistical Decision Tree
Author :
Wang, Kejian ; Teng, Guifa ; Huang, Dongmei ; Chang, Shuhui ; An, Xiurong ; Sun, Xinsheng
Author_Institution :
Sch. of Inf. Sci. & Technol., Agricultural Univ. of Hebei, Baoding
Abstract :
This paper introduces an algorithm based on Bayesian statistics and statistical decision tree (SDT) to recognize illegal E-mails. At first, Bayesian statistics can filter some specific words which are often used in illegal E-mails. Then, SDT can determine illegal E-mails by Semanteme analyse. After those two process, the illegal E-mails can also be easily determined and the recognition rate of illegal E-mails has been improved
Keywords :
Bayes methods; decision trees; electronic mail; security of data; Bayesian statistics; Semanteme analyse; illegal E-mails recognition; statistical decision tree; Bayesian methods; Decision trees; Electronic mail; Filters; Frequency; Information science; Internet; Postal services; Statistics; Unsolicited electronic mail;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614617
