Washington: Researchers at Concordia University have proposed a new method to get rid of unwanted emails in inboxes.
PhD candidate Ola Amayri and thesis supervisor, Nizar Bouguila have now proposed a new statistical framework for spam filtering that quickly and efficiently blocks unwanted messages.
"The majority of previous research has focused on the textual content of spam emails, ignoring visual content found in multimedia content, such as images. By considering patterns from text and images simultaneously, we``ve been able to propose a new method for filtering out spam," says Amayri.
By conducting extensive experiments on traditional spam filtering methods that were general and limited to patterns found in texts or images, the researchers has developed a much stronger way, based on techniques used in pattern recognition and data mining, to filter out unwanted emails.
Although the new method has been tested on English spam emails, Amayri says it can be easily extended to other languages.
“Our new method for spam filtering is able to adapt to the dynamic nature of spam emails and accurately handle spammers`` tricks by carefully identifying informative patterns, which are automatically extracted from both text and images content of spam emails,” says Amayri.
While this new spam-detecting approach is still in the development stage, Amayri and Bouguila are also currently working on a plug-in for SpamAssassin, the world``s most widely used open-source spam filter.