TY  - BOOK
AU  - Lerma,L.Octavio
AU  - Kreinovich,Vladik
ED  - SpringerLink (Online service)
TI  - Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data
T2  - Studies in Big Data,
SN  - 9783319613499
AV  - Q342 
U1  - 006.3 23
PY  - 2018///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Computational intelligence
KW  - Data mining
KW  - Big data
KW  - Artificial intelligence
KW  - Computational Intelligence
KW  - Data Mining and Knowledge Discovery
KW  - Big Data
KW  - Big Data/Analytics
KW  - Artificial Intelligence
N1  - Acceso multiusuario; Introduction --  Data Acquisition: Towards Optimal Use of Sensors -- Data and Knowledge Processing --  Knowledge Propagation and Resulting Knowledge Enhancement -- Knowledge Use -- Conclusions
N2  - 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
UR  - http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-61349-9
ER  -