Sciweavers

Share
SAC
2009
ACM

Spam decisions on gray e-mail using personalized ontologies

9 years 4 months ago
Spam decisions on gray e-mail using personalized ontologies
E-mail is one of the most common communication methods among people on the Internet. However, the increase of e-mail misuse/abuse has resulted in an increasing volume of spam e-mail over recent years. As spammers always try to find a way to evade existing spam filters, new filters need to be developed to catch spam. A statistical learning filter is at the core of many commercial anti-spam filters. It can either be trained globally for all users, or personally for each user. Generally, globally-trained filters outperform personally-trained filters for both small and large collections of users under a real environment. However, globally-trained filters sometimes ignore personal data. Globallytrained filters cannot retain personal preferences and contexts as to whether a feature should be treated as an indicator of legitimate e-mail or spam. Gray e-mail is a message that could reasonably be considered either legitimate or spam. In this paper, a personalized ontology spam filter was imple...
Seongwook Youn, Dennis McLeod
Added 23 Jul 2010
Updated 23 Jul 2010
Type Conference
Year 2009
Where SAC
Authors Seongwook Youn, Dennis McLeod
Comments (0)
books