Using word similarity to eradicate junk emails
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Personalized email recommender system based on user actions
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
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When the average number of spam messages received is continually increasing exponentially, both the Internet Service Provider and the end user suffer[1-3]. The lack of an efficient solution may threaten the usability of the email as a communication means. In this paper we present a filtering mechanism applying the idea of preference ranking. This filtering mechanism will distinguish spam emails from other email on the Internet. The preference ranking gives the similarity values for nominated emails and spam emails specified by users, so that the ISP/end users can deal with spam emails at filtering points. We designed three filtering points to classify nominated emails into spam email, unsure email and legitimate email. This filtering mechanism can be applied on both middleware and at the client-side. The experiments show that high precision, recall and TCR (total cost ratio) of spam emails can be predicted for the preference based filtering mechanisms.