MAIL CONTENT FILTERING USING MACHINE LEARNING ALGORITHMS IN BIG DATA ENVIRONMENTS

Abstract

Email spam is an operation that sends different email clients to undesirable messages. Email spam is one of the problems for every individual. Email spam is adware for any company/product or any type that receives any notification without an email client mailbox. The spam filtering techniques were used to solve these kinds of problems. Thus, the spam filtering technique will protect your mailbox from spam mail. Here, we use the Support Vector Machine it is a Classifier structured as three-layered frameworks that include bulk emails for spam classification for obfuscator, classifier, and anomaly This Support Vector Machine is such a simple and highly efficient method for spam. Here we will use the classification of spam and non-spam emails for real-time. The extraction technique consists of features such as being used to extract the features of the digestive that are based on the bucket. So that the result of this system is to increase and implement the Self-Acknowledgeable Intranet Mail System that had been designed and it is made for the benefit of the status of the sender. When the mail is sent, the recipient's activity is known by the sender until the mail system is reviewed. And at last, here we provide a pop-up window that is used to identify the spam emails at the time of the mail content.