株式会社極東書店トップ ＞ 商品一覧 ＞ Applications of Big Data Analytics: Trends, Issues, and Challenges. 2018 ed.
商品詳細
Applications of Big Data Analytics: Trends, Issues, and Challenges. 2018 ed.
・ISBN 978-3-319-76471-9 hard EUR 109.99
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| 著者・編者 | Alani, Mohammed M. / Tawfik, Hissam / Saeed, Mohammed / Anya, Obinna (eds.), |
|---|---|
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2018 |
| ページ数 | 214 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-61899＞ |
解説
This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.
Topics and features:
- Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing
- Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants
- Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios
- Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders
- Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices
- Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment