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Journal ArticleDOI

Survey on Spam Filtering Techniques and Mapreduce

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TLDR
This paper surveys different spam email filtering techniques and Machine learning based, list based, content based and hybrid or other is used because of high accuracy and mathematical support.
Abstract
Spam Email, also known as junk email , is a subset of electronic spam involving nearly identical messages sent to numerous recipients by email. The messages may contain disguised links that appear to be for familiar websites but in fact lead to phishing web sites or sites that are hosting malware. Spam email may also include malware as scripts or other executable file attachments. Spam is any unwanted and harmful mail. Separation of spam from normal mails is essential. This paper surveys different spam email filtering techniques. The different techniques are Machine learning based, list based, content based and hybrid or other. Machine learning based, is mostly used because of high accuracy and mathematical support. Keywords—Spam filtering techniques, Machine learning based ,content based, word based.

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References
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Journal ArticleDOI

An ontology enhanced parallel SVM for scalable spam filter training

TL;DR: Experimental results show that ontology based augmentation improves the accuracy level of the parallel SVM beyond the original sequential counterpart.
Proceedings ArticleDOI

Application of sim-hash algorithm and big data analysis in spam email detection system

TL;DR: A novel similarity-based method is proposed that implements the fingerprinting technique on parallel processing framework and meet-in-the-middle approach is used in this method to achieve a higher accuracy in the spam email detection system.