Index

Table of Contents
1	The history of spam	3
2	Historical approaches to fighting spam	25
3	Language classification concepts	45
4	Statistical filtering fundamentals	63
5	Decoding : uncombobulating messages	87
6	Tokenization : the building blocks of spam	97
7	The low-down dirty tricks of spammers	111
8	Data storage for a zillion records	141
9	Scaling in large environments	157
10	Testing theory	177
11	Concept identification : advanced tokenization	197
12	Fifth-order Markovian discrimination	215
13	Intelligent feature set reduction	227
14	Collaborative algorithms	241
App	Shining examples of filtering	257