DocumentCode :
2346992
Title :
Spam Mail Classification Using Combined Approach of Bayesian and Neural Network
Author :
Manjusha, K. ; Kumar, Rakesh
Author_Institution :
Comput. Sci. & Inf. Syst. Group, Birla Inst. of Technol. & Sci., Pilani, India
fYear :
2010
fDate :
26-28 Nov. 2010
Firstpage :
145
Lastpage :
149
Abstract :
Unsolicited commercial e-mail (spam) has shocked economies world over and is threatening the productivity. In this paper, an attempt has been made to classify email spam by combining Bayesian network and neural network classification approach. The header information like sender details and origin IP etc. was analyzed by centered Bayesian network, whereas the content and subject of the email were separately analyzed to classify the e-mail by neural network as a classifier trained by genetic algorithm (GA).
Keywords :
belief networks; genetic algorithms; neural nets; pattern classification; unsolicited e-mail; Bayesian network; genetic algorithm; neural network; spam mail classification; unsolicited bulk email; Centered Bayesian Network; Spam Filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Communication Networks (CICN), 2010 International Conference on
Conference_Location :
Bhopal
Print_ISBN :
978-1-4244-8653-3
Electronic_ISBN :
978-0-7695-4254-6
Type :
conf
DOI :
10.1109/CICN.2010.39
Filename :
5701953
Link To Document :
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