Mobile Data Mining and Applications / by Hao Jiang, Qimei Chen, Yuanyuan Zeng, Deshi Li
By: Jiang, Hao, autor
Contributor(s): SpringerLink (Online service)
| Chen, Qimei., autor | Li, Deshi., autor | Zeng, Yuanyuan., autor
Series: (Engineering (Springer-11647)); (Information Fusion and Data Science, 2510-1528).Publisher: Cham : Springer, 2019Description: 1 recurso en línea (X, 227 páginas) : 96 ilustraciones, 77 ilustraciones a color.ISBN: 9783030165031.Subject: Data mining
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA76.9 .D343 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBooks24062348 |
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| QA76.9.D343 2017 EB Phrase Mining from Massive Text and Its Applications | QA76.9.D343 2018 EB Traffic Mining Applied to Police Activities : Proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) | QA76.9 .D343 2018 EB Mining Structures of Factual Knowledge from Text : An Effort-Light Approach | QA76.9 .D343 2019 EB Mobile Data Mining and Applications | QA76.9 .D343 2019 EB Searching Speech Databases : Features, Techniques and Evaluation Measures | QA76.9.D343 2019 EB Linking and Mining Heterogeneous and Multi-view Data | QA76.9 .D343 2019 EB Innovations in Infrastructure : Proceedings of ICIIF 2018 |
Chapter1: Introduction -- Chapter2: Mobile Data Processing and Feature Discovery -- Chapter3: Mobile Data Application in Wireless Communication -- Chapter4: Mobile Data Application in Mobile Network -- Chapter5: Mobile Data Application in Smart City -- Chapter6: Conclusion, Remarks and Future Directions.
This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities. In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.
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