The Naïve Bayes Model for Unsupervised Word Sense Disambiguation Aspects Concerning Feature Selection /

This book presents recent advances (from 2008 to 2012) concerning use of the Naïve Bayes model in unsupervised word sense disambiguation (WSD). While WSD, in general, has a number of important applications in various fields of artificial intelligence (information retrieval, text processing, machine...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: T. Hristea, Florentina (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:SpringerBriefs in Statistics,
Temas:
Statistics .
Computer science.
Artificial intelligence.
Statistics.
Computer Science.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 1.Preliminaries
  • 2.The Naïve Bayes Model in the Context of Word Sense Disambiguation
  • 3.Semantic WordNet-based Feature Selection
  • 4.Syntactic Dependency-based Feature Selection
  • 5.N-Gram Features for Unsupervised WSD with an Underlying Naïve Bayes Model References
  • Index.  .

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