Analysis Of Email Fraud Detection Using Weka Tool

Transcript

Data mining is also being useful to give solutions for invasion finding and auditing. While data mining has several applications in protection, there are also serious privacy fears. Because of email mining, even inexperienced users can connect data and make responsive associations. Therefore we must to implement the privacy of persons while working on practical data mining. Using K-mean clustering algorithm and weka tool we implemented the technique of Email-mining. The WEKA tool calls the .eml file format into text converter and then processed the whole data into preprocessor output in form of .csv file format. The preprocessor output shows the graphical results of the processed email data. The goal of this implementation is to detect or filter the email addresses from which we get maximum emails.