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AIRWEB
2009
Springer
14 years 4 months ago
Looking into the past to better classify web spam
Web spamming techniques aim to achieve undeserved rankings in search results. Research has been widely conducted on identifying such spam and neutralizing its influence. However,...
Na Dai, Brian D. Davison, Xiaoguang Qi
JCS
2010
135views more  JCS 2010»
13 years 8 months ago
New filtering approaches for phishing email
Phishing emails usually contain a message from a credible looking source requesting a user to click a link to a website where she/he is asked to enter a password or other confide...
André Bergholz, Jan De Beer, Sebastian Glah...
CEAS
2007
Springer
14 years 1 months ago
Learning Fast Classifiers for Image Spam
Recently, spammers have proliferated "image spam", emails which contain the text of the spam message in a human readable image instead of the message body, making detect...
Mark Dredze, Reuven Gevaryahu, Ari Elias-Bachrach
CEAS
2005
Springer
14 years 3 months ago
Combating Spam through Legislation: A Comparative Analysis of US and European Approaches
Unsolicited Commercial Communication also known as spam - has traditionally been the most visible e-mail threat and has reached a point where it creates a major problem for the de...
Evangelos Moustakas, C. Ranganathan, Penny Duqueno...
CORR
2000
Springer
126views Education» more  CORR 2000»
13 years 9 months ago
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
We investigate the performance of two machine learning algorithms in the context of antispam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee...
Ion Androutsopoulos, Georgios Paliouras, Vangelis ...