Mobile Data Mining and Applications

• Κύριοι συγγραφείς: Jiang, Hao (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Chen, Qimei (http://id.loc.gov/vocabulary/relators/aut), Zeng, Yuanyuan (http://id.loc.gov/vocabulary/relators/aut), Li, Deshi (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Information Fusion and Data Science,
• Θέματα: Wireless communication systems.; Mobile communication systems.; Sociophysics.; Econophysics.; Data mining.; Electrical engineering.; Mobile computing.; Urban geography.; Wireless and Mobile Communication.; Data-driven Science, Modeling and Theory Building.; Data Mining and Knowledge Discovery.; Communications Engineering, Networks.; Mobile Computing.; Urban Geography / Urbanism (inc. megacities, cities, towns).

 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. 

 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.