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Survey of Spam Filtering Techniques and Tools, and MapReduce with SVM?

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.2, No. 11)

Publication Date:

Authors : ;

Page : 91-98

Keywords : Spam filtering techniques; Naïve Bayes classifier; Support Vector Machine (SVM); Neural Networks (NN); K-Nearest Neighbor (KNN); spam filtering tools; MapReduce;

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Spam is unsolicited, junk email with variety of shapes and forms. To filter spam, various techniques are used. Techniques like Naïve Bayesian Classifier, Support Vector Machine (SVM) etc. are often used. Also, a number of tools for spam filtering either paid or free are available. Amongst all techniques SVM is mostly used. SVM is computationally intensive and for training it can’t work with large a dataset, these cons can be minimized by introducing MapReduce framework for SVM. MapReduce framework can work in parallel with input dataset file chunks to train SVM for time reduction. This paper aims at surveying of few such techniques and popular spam filtering tools with scope to introduce MapReduce with SVM.

Last modified: 2013-11-20 15:25:05