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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
USENIX
2003
13 years 6 months ago
Learning Spam: Simple Techniques For Freely-Available Software
The problem of automatically filtering out spam e-mail using a classifier based on machine learning methods is of great recent interest. This paper gives an introduction to mach...
Bart Massey, Mick Thomure, Raya Budrevich, Scott L...
CEAS
2007
Springer
13 years 11 months ago
Filtering Image Spam with Near-Duplicate Detection
A new trend in email spam is the emergence of image spam. Although current anti-spam technologies are quite successful in filtering text-based spam emails, the new image spams ar...
Zhe Wang, William K. Josephson, Qin Lv, Moses Char...
AIRWEB
2008
Springer
13 years 7 months ago
Identifying web spam with user behavior analysis
Combating Web spam has become one of the top challenges for Web search engines. State-of-the-art spam detection techniques are usually designed for specific known types of Web spa...
Yiqun Liu, Rongwei Cen, Min Zhang, Shaoping Ma, Li...
ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
13 years 11 months ago
Detecting Link Spam Using Temporal Information
How to effectively protect against spam on search ranking results is an important issue for contemporary web search engines. This paper addresses the problem of combating one majo...
Guoyang Shen, Bin Gao, Tie-Yan Liu, Guang Feng, Sh...