Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data

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Éditeur :

Springer


Collection :

Studies in Big Data

Paru le : 2017-08-19

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Description

This book describes analytical techniques for optimizing knowledge acquisition, processing, and propagation, especially in the contexts of cyber-infrastructure and big data. Further, it presents easy-to-use analytical models of knowledge-related processes and their applications.
The need for such methods stems from the fact that, when we have to decide where to place sensors, or which algorithm to use for processing the data—we mostly rely on experts’ opinions. As a result, the selected knowledge-related methods are often far from ideal. To make better selections, it is necessary to first create easy-to-use models of knowledge-related processes. This is especially important for big data, where traditional numerical methods are unsuitable.
The book offers a valuable guide for everyone interested in big data applications: students looking for an overview of related analytical techniques, practitioners interested in applying optimization techniques, and researchers seeking to improve and expand on these techniques.
Pages
141 pages
Collection
Studies in Big Data
Parution
2017-08-19
Marque
Springer
EAN papier
9783319613482
EAN PDF
9783319613499

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
14
Taille du fichier
1946 Ko
Prix
116,04 €
EAN EPUB
9783319613499

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
14
Taille du fichier
1792 Ko
Prix
116,04 €