Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data (Record no. 75391)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03486nam a22006015i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-61349-9 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220801213619.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 170820s2018 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319613499 |
| -- | 978-3-319-61349-9 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 100 1# - AUTHOR NAME | |
| Author | Lerma, L. Octavio. |
| 245 10 - TITLE STATEMENT | |
| Title | Towards Analytical Techniques for Optimizing Knowledge Acquisition, Processing, Propagation, and Use in Cyberinfrastructure and Big Data |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2018. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | VIII, 141 p. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Studies in Big Data, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Data Acquisition: Towards Optimal Use of Sensors -- Data and Knowledge Processing -- Knowledge Propagation and Resulting Knowledge Enhancement -- Knowledge Use -- Conclusions. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Kreinovich, Vladik. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-319-61349-9 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2018. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big data. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Quantitative research. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big Data. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Analysis and Big Data. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2197-6511 ; |
| 912 ## - | |
| -- | ZDB-2-ENG |
| 912 ## - | |
| -- | ZDB-2-SXE |
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