A COMPARATIVE STUDY ON DIFFERENT EMAIL SPAM FILTERING TECHNIQUES
Keywords:
Spams, Spam Filtering, Naive Bayesian Filter, Support Vector Machines, Decision Trees, Negative SelectionAbstract
An ideal spam filter is difficult to achieve, that is one which filter out any type of spam at any time. Most of the anti spam solutions fails to filter new types of spam. This is because whenever researchers introduce new filtering mechanisms spammers deploy new spamming techniques which can bypass those filters. In this scenario one thing possible is to update the current filtering mechanisms and minimize the security breaches. This study focuses on analyzing different data mining based classification algorithms which can be used for spam filtering and find out how effective they are.
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