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Ending Spam – Bayesian Content Filtering and the Art of Statistical Language Classification - Softcover
Synopsis
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.
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About the Author
Jonathan A. Zdziarski has been fighting spam for eight years, and has spent a significant portion of the past two years working on the next generation spam filter DSPAM, with up to 99.985% accuracy. Zdziarski lectures widely on the topic of spam.
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Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification
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Ending Spam: Bayesian Content Filtering and the Art of Statistical Language Classification
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Ending Spam
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