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Text mining & natural language understanding at Scale : building Scalable NLP pipelines with Scala & Spark /

"A text mining system must go way beyond indexing and search to appear truly intelligent. First, it should understand language beyond keyword matching. For example, it should be able to distinguish the critical difference between 'Jane has the flu' and 'Jane had the flu when she...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly, [2016]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Talby, David,  |e on-screen presenter. 
245 1 0 |a Text mining & natural language understanding at Scale :  |b building Scalable NLP pipelines with Scala & Spark /  |c with David Talby & Claudiu Branzan. 
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520 |a "A text mining system must go way beyond indexing and search to appear truly intelligent. First, it should understand language beyond keyword matching. For example, it should be able to distinguish the critical difference between 'Jane has the flu' and 'Jane had the flu when she was 9'. Second, it should be capable of making likely inferences even if they're not explicitly written. For example, inferring that Jan may have the flu if she has had a fever, headache, fatigue, and runny nose for three days. And third, it should do its work as part of a robust, scalable, efficient and easy to extend system. This course teaches software engineers and data scientists how to build intelligent natural language understanding (NLU) based text mining systems at scale using Java, Scala and Spark for distributed processing."--Resource description page. 
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