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.

[1]  Benchaphon Limthanmaphon,et al.  Fast Effective Botnet Spam Detection , 2009, 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology.

[2]  Vidyasagar Potdar,et al.  Evaluation of spam detection and prevention frameworks for email and image spam: a state of art , 2008, iiWAS.

[3]  El-Sayed M. El-Alfy,et al.  Using GMDH-based networks for improved spam detection and email feature analysis , 2011, Appl. Soft Comput..

[4]  Miguel Rio,et al.  Symbiotic filtering for spam email detection , 2011, Expert Syst. Appl..

[5]  Dawn Xiaodong Song,et al.  Design and Evaluation of a Real-Time URL Spam Filtering Service , 2011, 2011 IEEE Symposium on Security and Privacy.

[6]  Pang-Ning Tan,et al.  History-Based Email Prioritization , 2009, 2009 International Conference on Advances in Social Network Analysis and Mining.

[7]  Dan Klein,et al.  Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network , 2003, NAACL.

[8]  Ming-Syan Chen,et al.  Incremental SVM Model for Spam Detection on Dynamic Email Social Networks , 2009, 2009 International Conference on Computational Science and Engineering.