Spam Filtering Based on Variable Precision Rough Set Decision Tree

Authors

Wang Jing, 1. College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;;
Xingwei Wang, 1. College of Computer Science and Engineering, Northeastern University, Shenyang 110819, China;;2. College of Software, Northeastern University, Shenyang 110819, China;;
Zhao Yue, 3. Network Service, Liaoning University, Shenyang 110036, China;

Abstract

Abstract: Email is favored by people and has become one of the most universal information communication methods, inspired by its convenience and low cost. However, E-mail has also been abused by malicious people. As a result, Internet has been polluted by spam. Spam not only wastes bandwidth resource, disrupting people's normal life and work, but also influences routine application of mail servers and poses a serious threat to Internet security. Decision tree algorithm was utilized to train extracted mail head feature information to construct a decision tree, which could be further used to filter spam. Variable precision rough set model was introduced to classify some specific instance or noise data into appropriate class, avoiding the situation when normal mails were regarded as junk mails, reducing losses bringing to users. As is shown in the result, the proposed algorithm is feasible in spam filtering and decreases the rate of normal mails being regarded as junk.

Recommended Citation

Jing, Wang; Wang, Xingwei; and Yue, Zhao (2020) "Spam Filtering Based on Variable Precision Rough Set Decision Tree," Journal of System Simulation: Vol. 28: Iss. 3, Article 27.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss3/27

First Page

705

Revised Date

2014-10-27

DOI Link

https://doi.org/

Last Page

710

CLC

TP391.9

Recommended Citation

Wang Jing, Wang Xingwei, Zhao Yue. Spam Filtering Based on Variable Precision Rough Set Decision Tree[J]. Journal of System Simulation, 2016, 28(3): 705-710.