conventional mail filtering techniques based on unsupervised learning where the classification is done on the basis keyword matching. But if spammers change the tricks of spam mails framing than the old classifiers will than not able to give the accurate results. That is the worst part of the unsupervised learning. On the other hand, in the same paper, machine learning techniques based on supervised learning is introduced where the classifiers are regularly fed with the changing patterns of spam mails with
Introduction Let’s start by defining spam; irrelevant or inappropriate messages sent on the Internet to a large number of recipients. Microsoft defines spam as an unwanted email trying to get information or sell you something [1]. This could be a fake email from your bank saying you need to authorize yourself, or even just a flyer trying to sell you anything from male enhancement to clothing. Next up let’s explain how to prevent spam mail. According to Vitaly Friedman the single biggest and easiest
AND e-MAIL Anyone who "SPAMS" as a marketing technique should be forced to sit at a computer and experience the utter agony that is receiving SPAM email. In the past week I have received over 105 emails to my AOL account. Out of the 105 emails, only one was a "real" email from an actual person, the rest: SPAM! This problem must be happening to others, so why hasn't something been done to outlaw this annoying junk email? Who is the evil mastermind behind this so-called "SPAM"? Who is it, so I can
1. Introduction Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning