Sciweavers

6 search results - page 1 / 2
» Evaluating cost-sensitive Unsolicited Bulk Email categorizat...
Sort
View
HIS
2004
13 years 7 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 7 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»
14 years 4 days 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...