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HIS
2004
15 years 3 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
CCS
2010
ACM
15 years 2 months ago
@spam: the underground on 140 characters or less
In this work we present a characterization of spam on Twitter. We find that 8% of 25 million URLs posted to the site point to phishing, malware, and scams listed on popular blackl...
Chris Grier, Kurt Thomas, Vern Paxson, Michael Zha...
AIRWEB
2007
Springer
15 years 8 months ago
Transductive Link Spam Detection
Web spam can significantly deteriorate the quality of search engines. Early web spamming techniques mainly manipulate page content. Since linkage information is widely used in we...
Dengyong Zhou, Chris Burges, Tao Tao
WWW
2008
ACM
16 years 2 months ago
User behavior oriented web spam detection
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, Min Zhang, Shaoping Ma, Liyun Ru
AIRWEB
2005
Springer
15 years 7 months ago
Blocking Blog Spam with Language Model Disagreement
We present an approach for detecting link spam common in blog comments by comparing the language models used in the blog post, the comment, and pages linked by the comments. In co...
Gilad Mishne, David Carmel, Ronny Lempel