Bayesian Content Filtering and the Art of Statistical Language Classification

1. Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification
   
2. byJonathan A. Zdziarski
   
3. No Starch Press 2005 (312 pages)
   
4. ISBN:1593270526
   
5. If you’re a programmer designing a new spam filter, a network admin implementing a spam-filtering solution, or just curious about how spam filters work and how spammers evade them, this landmark book serves as a helpful study of the war against spammers.
   
6. 
   
7. Table of Contents  
   
8. Ending Spam—Bayesian Content Filtering and the Art of Statistical Language Classification  
   
9. Introduction  
   
10. Part I - An Introduction To Spam Filtering
    
11. Chapter 1 - The History Of Spam
    
12. Chapter 2 - Historical Approaches To Fighting Spam
    
13. Chapter 3 - Language Classification Concepts
    
14. Chapter 4 - Statistical Filtering Fundamentals
    
15. Part II - Fundamentals Of Statistical Filtering
    
16. Chapter 5 - Decoding: Uncombobulating Messages
    
17. Chapter 6 - Tokenization: The Building Blocks Of Spam
    
18. Chapter 7 - The Low-Down Dirty Tricks Of Spammers
    
19. Chapter 8 - Data Storage For A Zillion Records
    
20. Chapter 9 - Scaling In Large Environments
    
21. Part III - Advanced Concepts Of Statistical Filtering
    
22. Chapter 10 - Testing Theory
    
23. Chapter 11 - Concept Identification—Advanced Tokenization
    
24. Chapter 12 - Fifth - Order Markovian Discrimination
    
25. Chapter 13 - Intelligent Feature Set Reduction
    
26. Chapter 14 - Collaborative Algorithms
    
27. Appendix - Shining Examples Of Filtering
    
28. Index  
    
29. List of Figures  
    
30. List of Tables  
    
31. List of Listings  

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