Email Classification using Classification Method

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2016 by IJETT Journal
Volume-32 Number-3
Year of Publication : 2016
Authors : Mis.Elifenesh Yitagesu, Prof Manisha Tijare
DOI :  10.14445/22315381/IJETT-V32P226

Citation 

Mis.Elifenesh Yitagesu, Prof Manisha Tijare"Email Classification using Classification Method", International Journal of Engineering Trends and Technology (IJETT), V32(3),142-145 February 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Electronic mail message became progressively vital and widespread technique communication due to its time speed. And its traffic has risen exponentially with the appearance of WWW. The more and more in email traffic comes additionally with an increasing the utilization emails for illegitimate purpose sizable amount of spam email are inflicting significant issue for web user and web service. Spam is unwanted or a bad email. And email users daily receive more spam email rather than ham email. For this reason we should have to use effective spam filtering technique are based on data classification. This technique is used to classify email as spam and legitimate. To test various classification rules we have use the WEKA interface.

 References

[1] MinyiGuo,Yang Xiang Mid Rafiqul Islam wanlei Zhou, "An innovative analyser for multi classifier e-mail classification based on grey list analysis," Journal of Network and computer Application, feabruary 2008.
[2] Rafiqul Islam and Yang Xiang, "Email Classification using Data Reduction method".
[3] Rekhan, SandeepNegi, "Areview on different spam detection approaches ," international journal of engineering trend and technology, vol. 11, may 2014.
[4] W.A. Awad1 and S.M. ELseuofi, "Machine Learning Methods for Spam E-mail Classification," international jornal of computer science and information technology, vol. 3, February 2011.
[5] savitapundalkiteki, santoshkumarbiradar, "effective email classification for spam and non-spam," international journal of advanced research in computer science and software engineering, vol. 4, no. 6, june 2014.
[6] Mrs. Pranjal S. Bogawar, Dr. Kishor. K. Bhoyar, "Email mining: A Review," international journal of computer science issues, vol. 9, no. 1, pp. 429-434, january 2012.
[7] AbhaSuryavanshi, ShishirShandilya, "spam filtering and removing spam content from message by using naive bayesian," international journal of computational engineering and managment , vol. 15, pp. 104-109, july 2012.
[8] S. Roy, A. Patra, S.Sau, K.Mandal, S. Kunar, "an efficient spam filtering techniques for email account," american journal of engineering research, vol. 02, no. 10, pp. 63-73, 2013.
[9] Matthew Chang, Chung Keung Poon *, "using phrases as features in email classification," the journal of system and software, january 2009.
[10] Mohammed A.Naser, AtharH.Mohammed, "Emails classification by data mining techniques ," Journal of Babylon University/Pure and Applied Sciences, vol. 22, 2014.
[11] Jian Pei, and Wo-Shun LukGuanting Tang, "Email Mining: Tasks, Common Techniques, and Tools," april 2013.
[12] Ravi KalkindriSujeet More, "evaluation of deceptive mails using filtering and weka," IEEE sponsored 2nd international conference on innovation in information embedded and communication system ICIIECS`15, 2015.

Keywords
classifier, email, spam and ham email, future selection