E-mail Classification Using Genetic Algorithm with Heuristic Fitness Function

International Journal of Computer Trends and Technology (IJCTT)          
© - August Issue 2013 by IJCTT Journal
Volume-4 Issue-8                           
Year of Publication : 2013
Authors :Jitendra Nath Shrivastava, Maringanti Hima Bindu


Jitendra Nath Shrivastava, Maringanti Hima Bindu"E-mail Classification Using Genetic Algorithm with Heuristic Fitness Function"International Journal of Computer Trends and Technology (IJCTT),V4(8):2956-2961 August Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract:- Internet users use e-mail to communicate over internet. They rely on the mail system to deliver their mails to the recipient. Spam has made the mail system more unreliable and unpredictable. It is the biggest threat to the e-mailing users. Spam has increased enormously in the last few years. Presently, the spam has an important role for users of email. It is really very hard to design an anti-spam solution that could be useful in stopping the spam completely. Most mail can get falsely caught by spam filters on the way to the recipient or it can drown among spam in the recipients’ inbox. A general definition of spam does not occur because spam is different for every user. The Internet community needs to work to prevent spam. Possible ways to do this are through the law and the legal system, technical solutions and user awareness. In past, several statistical methods have been used, and have shown great performance, excelling in adapting to the ever changing content of SPAM e-mail. Still a perfect solution is not available till date. In this paper, a genetic algorithm based e-mail filtration method is presented, and method is tested on 1108 emails and efficiency of the method is found to be nearly 82%.


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Keywords : Hierarchical Matching, Calligraphic Retrieval, Skeleton Similarity