Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification

By Jonathan Zdziarski. 2005

101 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Christopher Krügel
2. Engin Kirda
3. Zi Chu
4. Steven Gianvecchio
5. Sushil Jajodia
6. Günther Bayler
7. Christoph Karlberger
8. Haining Wang

Citations in the corpus

• Exploiting Redundancy in Natural Language to Penetrate Bayesian Spam Filters (2007, methodology): “We first examine whether this precondition is met; afterwards, we measure the effectivity of an automated substitution attack by creating a test set of spam messages that are tested against SpamAssassin, DSPAM, and Gmail.”
• Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg? (2012, background): “In addition, as Twitter is text-based, e-mail spam filtering techniques are also relevant [27], [28], [29].”