User History Based Mail Filtering Process

Email spams are probable intimidation to an email user. In this paper we deal with spams which may slither through filters into client's mailbox (false negative). We use client's history to solve the above mentioned problem. For a client a particular message can be important while for some other client they may be unimportant. Other than filtered spam generally a user decides which type of message is spam by flagging it. Our novel approach reduces this effort and client need not see all mails and manually flag them as spam because this filtering system and algorithms used in it will separate all those junks so that the client is left with only those mails which are useful for him/her. We propose using, part of speech tagging module of Natural Language Processing and some other discussed algorithms. This approach is not only saving time of a client but is also acting as a good mail filter.