Ending spam : Bayesian content filtering and the art of statistical language classification /

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 algorithm...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Zdziarski, Jonathan A.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: San Francisco : No Starch Press, 2005.
Edición:1st ed.
Temas:
Spam filtering (Electronic mail)
Filters (Mathematics)
Pourriels > Filtrage.
Filtres (Mathématiques)
COMPUTERS > Data Processing.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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.

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