Content-Based Clustering of E-Mail : Refinement Using Data Mining

Nowadays, communication among people happens largely through computer. E-mail is one such method. The usual problem that users face in this method is unwanted messages. This happens because advertisers and others send bulk messages to a large number of e-mail addresses. When the number of unwanted e-mails increases, it takes more time and effort for the users to read them. In this situation, there are chances that the user might miss important messages due to the large number of unwanted or unimportant e-mails in their mailbox. This paper discusses dynamic message filtering, such as filtering incoming messages in response to their content; in one embodiment, messages can be delivered to their respective categories based on the content, which are predefined by the user as a part of dynamic filtering. This paper presents a software that filters all the incoming messages dynamically and classifies them to the classified folders predefined by the user - Jobs, Resume, Friends, and so on. The users can define their own categories of messages. The application receives the filtered messages and redirects them based on the content to the respective categories