Ending Spam: Bayesian Content Filtering and the Art of Statistical Language ClassificationNo Starch Press, 2005 - 312 lappuses Through considerable research, creative minds have invented 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 spam. Zdziarski explains how spam filtering works and how language classification and machine learning combine to produce remarkably accurate spam filters. 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. Interviews with the creators of many of the best spam filters provide further insight into the anti-spam crusade. |
Saturs
PART II FUNDAMENTALS OF STATISTICAL FILTERING | 85 |
PART III ADVANCED CONCEPTS OF STATISTICAL FILTERING | 175 |
APPENDIX SHINING EXAMPLES OF FILTERING | 257 |
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