Ending Spam by Jonathan Zdziarski
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Ending Spam
By Jonathan Zdziarski

Ending Spam

Bayesian Content Filtering and the Art of Statistical Language Classification

By (author) See other recent books by Jonathan Zdziarski
Format: Paperback

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Ending Spam by Jonathan Zdziarski

Book Description

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. TOC Introduction PART I: An Introduction to Spam Filtering Chapter 1: The History of Spam Chapter 2: Historical Approaches to Fighting Spam Chapter 3: Language Classification Concepts Chapter 4: Statistical Filtering Fundamentals PART II: Fundamentals of Statistical Filtering Chapter 5: Decoding: Uncombobulating Messages Chapter 6: Tokenization: The Building Blocks of Spam Chapter 7: The Low-Down Dirty Tricks of Spammers Chapter 8: Data Storage for a Zillion Records Chapter 9: Scaling in Large Environments PART III: Advanced Concepts of Statistical Filtering Chapter 10: Testing Theory Chapter 11: Concept Identification: Advanced Tokenization Chapter 12: Fifth-Order Markovian Discrimination Chapter 13: Intelligent Feature Set Reduction Chapter 14: Collaborative Algorithms Appendix: Shining Examples of Filtering Index

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Book Details

ISBN: 9781593270520
ISBN-10: 1593270526
Format: Paperback
(230mm x 185mm x 20mm)
Pages: 312
Imprint: No Starch Press,US
Publisher: No Starch Press,US
Publish Date: 1-Jan-2005
Country of Publication: United States

Books By Author Jonathan Zdziarski

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» View all books by Jonathan Zdziarski


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