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Modeling Intention in Email Speech Acts, Information Leaks and Recommendation Models /

Everyday more than half of American adult internet users read or write email messages at least once. The prevalence of email has significantly impacted the working world, functioning as a great asset on many levels, yet at times, a costly liability. In an effort to improve various aspects of work-re...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Carvalho, Vitor R. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011.
Edición:1st ed. 2011.
Colección:Studies in Computational Intelligence, 349
Temas:
Acceso en línea:Texto Completo
Descripción
Sumario:Everyday more than half of American adult internet users read or write email messages at least once. The prevalence of email has significantly impacted the working world, functioning as a great asset on many levels, yet at times, a costly liability. In an effort to improve various aspects of work-related communication, this work applies sophisticated machine learning techniques to a large body of email data. Several effective models are proposed that can aid with the prioritization of incoming messages, help with coordination of shared tasks, improve tracking of deadlines, and prevent disastrous information leaks. Carvalho presents many data-driven techniques that can positively impact work-related email communication and offers robust models that may be successfully applied to future machine learning tasks.
Descripción Física:XII, 104 p. online resource.
ISBN:9783642199561
ISSN:1860-9503 ;