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Ending Spam: Bayesian Content Filtering And The Art Of Statistical Language Classification

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.TOCIntroductionPART I: An Introduction to Spam FilteringChapter 1: The History of SpamChapter 2: Historical Approaches to Fighting SpamChapter 3: Language Classification ConceptsChapter 4: Statistical Filtering FundamentalsPART II: Fundamentals of Statistical FilteringChapter 5: Decoding: Uncombobulating MessagesChapter 6: Tokenization: The Building Blocks of SpamChapter 7: The Low-Down Dirty Tricks of SpammersChapter 8: Data Storage for a Zillion RecordsChapter 9: Scaling in Large EnvironmentsPART III: Advanced Concepts of Statistical FilteringChapter 10: Testing TheoryChapter 11: Concept Identification: Advanced TokenizationChapter 12: Fifth-Order Markovian DiscriminationChapter 13: Intelligent Feature Set ReductionChapter 14: Collaborative AlgorithmsAppendix: Shining Examples of FilteringIndex

Paperback: 312 pages

Publisher: No Starch Press; 1 edition (July 1, 2005)

Language: English

ISBN-10: 1593270526

ISBN-13: 978-1593270520

Product Dimensions: 7 x 0.7 x 9.2 inches

Shipping Weight: 1.1 pounds (View shipping rates and policies)

Average Customer Review: 4.3 out of 5 stars  See all reviews (14 customer reviews)

Best Sellers Rank: #2,184,821 in Books (See Top 100 in Books) #75 in Books > Computers & Technology > Hardware & DIY > Microprocessors & System Design > DSPs #231 in Books > Computers & Technology > Networking & Cloud Computing > Network Administration > Email Administration #272 in Books > Computers & Technology > Security & Encryption > Viruses

Ending Spam from Mr. Zdziarski is a well written BASIC and easy to understand INTRODUCTION to get a technical overview of todays spam fighting solutions on the market.Also it is written on the cover that it is f.e focused towards developers, network admins etc. I would consider the target customer to be IT Managers, or other curious people who want to get an overview.Thats what it does and it does it very well in my eyes.The book provides simplified, abstract overviews of some available spam filters solutions.The book is provided into 3 parts- An Introduction part to spam filtering (Chapter 1-4)- A part describing "Fundamentals of Statistical Filtering" (Chapter 5-9)- an the third part describing "Advanced Concepts of Statistical Filtering" (Chapter 10-14)Its a bit confusing that Chapter 4 has the same title than Part II. So perhaps Chapter 4 should have been part of "Part II" ?The Chapters which I found most interesting were:Chapter 4 "Fundamentals of Statistical Filtering"Chapter 7 "The Low down dirty Tricks of spammers"Chapter 9 "Scaling in Large Environments"I am sure the author could have easily filled the book with Chapter 7 alone. The book is very entertaining and has a nice motivating writing style. You might at times find some rant about the spammers which I have chosen to ignore as it doesnt contain any valuable information or anything which I didnt know already. While I might agree to some of the authors views, I believe that the rant does unfortunately do exactly the opposite in my eyes and does give spammers credit to how they do their work.

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