Intelligent e mail classification models for spam filtering using data mining techniques

Abstract

A commercial email sent to huge number of recipients is a Spam. The spam always takes up resources that cost money, such as bandwidth, and it serves the suppliers without any compensation. Spammers are persons or organizations that send extraneous message via internet. The spammers gather the email addresses of recipients from the newsgroup, websites and customer lists etc. The spams are intended to send advertisements, however, now it has become the trend that it is used for creating some serious problems such as security threats, phishing medium and also used to spread malicious software. To rectify these serious issues of spamming, researchers have been done automate the classification of emails. On the other hand, these areas are really challenging because the researcher needs to work with a huge number of unstructured information features, and enormous documents. When there is an increase in usage of these features, it will adversely affect the quality, speed and performance. There are numerous algorithms which are created by the researchers to restrict the spam, however, it can not be guaranteed that it will eliminate 100% spam from the recipitant mail. So, it is always difficult to choose the best algorithm. Data mining (sometime called as data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information. Data mining is the process of sorting through a large data sets to identify patterns and establish relationships to solve the problem through data analysis. This technology is used by organizations in order to help them to focus on the most powerful information of their data warehouse. The organizations use the data mining tool to forecast the drift and performance so that the business can make upbeat knowledge driven decision. newline newline newline