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E-book
Author Zdziarski, Jonathan A.

Title Ending spam : Bayesian content filtering and the art of statistical language classification / Jonathan A. Zdziarski
Edition 1st ed
Published San Francisco : No Starch Press, 2005
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Description 1 online resource (xx, 287 pages)
Contents An introduction to spam filtering concepts -- The history of spam -- Historical approaches to fighting spam -- Next generation filtering -- Shining examples of filtering -- Machine learning concepts -- Fundamentals of statistical filtering -- Statistical filtering fundamentals -- Decoding: uncombobulating messages -- Tokenization: the building blocks of spam -- Open source, OSX, and Milk Duds -- The low-down dirty details of spam -- Data storage for a zillion records -- Scaling for large-scale environments -- Advanced concepts of statistical filtering -- Concept identification: advanced tokenization -- Testing theory -- Fifth-order Markovian discrimination -- Concept identification: advanced tokenization -- Intelligent feature set reduction -- Collaborative algorithms -- Installing and using open source filters
Summary Ending Spam describes, in-depth, how statistical filtering is being used by next-generation spam filters to identify and filter unwanted email. Readers gain a complete understanding of the mathematical approaches used in today's spam filters, decoding, tokenization, the use of various algorithms (including Bayesian analysis and Markovian discrimination), and the benefits of using open source solutions to end spam
Notes Includes index
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL
English
digitized 2010 HathiTrust Digital Library committed to preserve pda MiAaHDL
Print version record
Subject Filters (Mathematics)
Spam filtering (Electronic mail)
COMPUTERS -- Data Processing.
Filters (Mathematics)
Spam filtering (Electronic mail)
Form Electronic book
LC no. 2005008221
ISBN 1593270852
9781593270858