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

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



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




Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification Jonathan Zdziarski
Language: English
Page: 312
Format: chm
ISBN: 1593270526, 9781593270520
Publisher: No Starch Press

Join author John Zdziarski for a look inside the brilliant minds that have conceived clever new ways to fight spam in all its nefarious forms. This landmark title describes, in-depth, how statistical filtering is being used by next-generation spam filters to identify and filter unwanted messages, how spam filtering works and how language classification and machine learning combine to produce remarkably accurate spam filters.

After reading Ending Spam, you’ll have a complete understanding of the mathematical approaches used by today’s spam filters as well as decoding, tokenization, various algorithms (including Bayesian analysis and Markovian discrimination) and the benefits of using open-source solutions to end spam. Zdziarski interviewed creators of many of the best spam filters and has included their insights in this revealing examination of the anti-spam crusade.

If you’re a programmer designing a new spam filter, a network admin implementing a spam-filtering solution, or just someone who’s curious about how spam filters work and the tactics spammers use to evade them, Ending Spam will serve as an informative analysis of the war against spammers.

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