Ending spam [[electronic resource] ] : Bayesian content filtering and the art of statistical language classification / / Jonathan A. Zdziarski

• Record Nr.: UNINA9910783398503321
• Autore: Zdziarski Jonathan A
• Pubbl/distr/stampa: San Francisco, : No Starch Press, 2005
• ISBN: 1-59327-085-2
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (314 p.)
• Disciplina: 005.7/13
• Soggetti: Spam filtering (Electronic mail); Filters (Mathematics)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Nota di contenuto: Preliminaries; Acknowledgments; Brief Contents; Contents In Detail; Introduction; The History Of Spam; Historical Approaches To Fighting Spam; Language Classification Concepts; Statistical Filtering Fundamentals; Decoding: Uncombobulating Messages; Tokenization: The Building Blocks Of Spam; The Low-down Dirty Tricks Of Spammers; Data Storage For A Zillion Records; Scaling In Large Environments; Testing Theory; Concept Identification: Advanced Tokenization; Fifth-order Markovian Discrimination; Intelligent Feature Set Reduction; Collaborative Algorithms; Shining Examples Of Filtering; Index
• Sommario/riassunto: 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.