Improving Spam Email Filtering Efficiency Using Bayesian Backward Approach Project

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Provided by: Interscience Open Access Journals
Topic: Security
Format: PDF
Unethical e-mail senders bear little or no cost for mass distribution of messages; yet normal e-mail users are forced to spend time and effort in reading undesirable messages from their mailboxes. Due to the rapid increase of electronic mail (or e-mail), several people and companies found it an easy way to distribute a massive amount of undesired messages to a tremendous number of users at a very low cost. These unwanted bulk messages or junk e-mails are called spam messages. Several machine learning approaches have been applied to this problem.
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