Efficient spam email filtering using adaptive ontology

被引:0
|
作者
Youn, Seongwook [1 ]
McLeod, Dennis [1 ]
机构
[1] Univ So Calif, Dept Comp Sci, Los Angeles, CA 90089 USA
基金
美国国家科学基金会;
关键词
spam; ontology; data mining; classification;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Email has become one of the fastest and most economical forms of communication. However, the increase of email users has resulted in the dramatic increase of spam emails during the past few years. As spammers always try to find a way to evade existing filters, newfilters need to be developed to catch spam. Ontologies allow for machine-understandable semantics of data It is important to share information with each other for more effective spam filtering. Thus, it is necessary to build ontology and a,framework for efficient email filtering. Using ontology that is specially designed to filter spam, bunch of unsolicited bulk email could be filtered out on the system. This paper proposes to find an efficient spam email filtering method using adaptive ontology.
引用
收藏
页码:249 / +
页数:2
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