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HIS
2004
13 years 6 months ago
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
Chih-Chin Lai, Ming-Chi Tsai
CORR
2000
Springer
71views Education» more  CORR 2000»
13 years 5 months ago
An evaluation of Naive Bayesian anti-spam filtering
It has recently been argued that a Naive Bayesian classifier can be used to filter unsolicited bulk e-mail ("spam"). We conduct a thorough evaluation of this proposal on...
Ion Androutsopoulos, John Koutsias, Konstantinos C...
AIPRF
2008
13 years 6 months ago
Spam Sender Detection with Classification Modeling on Highly Imbalanced Mail Server Behavior Data
Unsolicited commercial or bulk emails or emails containing viruses pose a great threat to the utility of email communications. A recent solution for filtering is reputation systems...
Yuchun Tang, Sven Krasser, Dmitri Alperovitch, Pau...
ICC
2007
IEEE
142views Communications» more  ICC 2007»
13 years 11 months ago
Filtering Spam Email Based on Retry Patterns
— A central problem in today’s Internet is unsolicited bulk email: spam. The SMTP protocol lacks a mechanism for verifying the source of a message, and respective protocol exte...
Peter Lieven, Björn Scheuermann, Michael Stin...