DocumentCode
1563446
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
Volume
1
fYear
2005
Firstpage
288
Lastpage
291
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614617
Filename
1614617
Link To Document