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SIGIR
2009
ACM
13 years 11 months ago
On the relative age of spam and ham training samples for email filtering
Email spam filters are commonly trained on a sample of spam and ham (non-spam) messages. We investigate the effect on filter performance of using samples of spam and ham messag...
Gordon V. Cormack, Jose-Marcio Martins da Cruz
CEAS
2011
Springer
12 years 4 months ago
Spam or ham?: characterizing and detecting fraudulent "not spam" reports in web mail systems
Web mail providers rely on users to “vote” to quickly and collaboratively identify spam messages. Unfortunately, spammers have begun to use bots to control large collections o...
Anirudh Ramachandran, Anirban Dasgupta, Nick Feams...
IAT
2008
IEEE
13 years 11 months ago
A Personalized Spam Filtering Approach Utilizing Two Separately Trained Filters
By feeding personal e-mails into the training set, personalized content-based spam filters are believed to classify e-mails in higher accuracy. However, filters trained by both sp...
Wei-Lun Teng, Wei-Chung Teng
CEAS
2008
Springer
13 years 6 months ago
Improving Image Spam Filtering Using Image Text Features
In this paper we consider the approach to image spam filtering based on using image classifiers aimed at discriminating between ham and spam images, previously proposed by other a...
Giorgio Fumera, Fabio Roli, Battista Biggio, Ignaz...
CEAS
2006
Springer
13 years 8 months ago
Online Discriminative Spam Filter Training
We describe a very simple technique for discriminatively training a spam filter. Our results on the TREC Enron spam corpus would have been the best for the Ham at .1% measure, and...
Joshua Goodman, Wen-tau Yih