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


Home > Mathematics Books > Bayesian Modelling > Item 16


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Click here to buy 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
by Jonathan Zdziarski
Sales Rank: 329891
4.0 out of 5 stars
List Price: $39.95
$30.36
At Amazon
on 12-5-2008
Buy Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification Now!

  • Paperback: 312 pages
  • Publisher: No Starch Press July 1, 2005
  • Language: English
  • ISBN-10: 1593270526
  • ISBN-13: 978-1593270520
  • Product Dimensions: 9.1 x 7 x 0.7 inches
  • Shipping Weight: 1.1 pounds

    Product Review
    A highly recommended read for anyone in charge of controlling spam in a corporate environment. -- Midwest Book Review, September 2005 (http://www.midwestbookreview.com/mbw/sep_05.htm)

    Does a good job of addressing advanced, complicated issues, but putting it in terms that readers can grasp. -- Netsecurity.about.com, August 29, 2005, http://netsecurity.about.com/od/5/fr/aabrendspam.htm

    Does a great job educating us on logic and thought taken to combat this SPAM blight on the Internet. -- MacCompanion, August 2005, 5 out of 5 stars

    Highly recommended read for anyone in charge of controlling spam in a corporate environment [and] on their own system. -- Readers Preference, readerspreference.com/reviews/endingspam.html

    IT managers who want a better understanding of how anti-spam products work should shell out the $39.95 price at once. -- eWeek, July 25, 2005

    If you’re looking for a primer on how the anti-spam battle is fought, you can’t do much better. -- InfoWorld, July 14, 2005,

    Leads the charge against what has become a very significant challenge to both productivity and sanity -- Book News, September 2005 (http://www.booknews.com/issues/sci-current.pdf)

    Not only enjoyable but actually captivating. -- Linux Magazine, October 2005 (http://www.linux-magazine.com/issue/59/Book_Reviews.pdf)

    The first book explaining the fine details of the theoretical models and machine-learning algorithms implemented in these filters. -- Slashdot, August 15, 2005

    This book is down, and dirty, loaded with information, and will make your head-hurt (in a good way). -- MyMac, August 29, 2005, mymac.com/showarticle.php?id=2074

    Product 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

  • Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification
    Available from Amazon
    Price: $30.36
    Updated on 12-5-2008

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


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