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020			_a9783030165031
024	7		_a10.1007/978-3-030-16503-1 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aQA76.9 .D343 _b2019 EB
100	1		_aJiang, Hao _eautor _9671321
245	1	0	_aMobile Data Mining and Applications _cby Hao Jiang, Qimei Chen, Yuanyuan Zeng, Deshi Li
264		1	_aCham _bSpringer _c2019
300			_a1 recurso en línea (X, 227 páginas) _b96 ilustraciones, 77 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
490	0		_aInformation Fusion and Data Science _x2510-1528
505	0		_aChapter1: 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.
520	3		_aThis 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.
650		7	_2embne _aData mining _9162648
700	1		_aChen, Qimei. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aLi, Deshi. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aZeng, Yuanyuan. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783030165024
776	0	8	_iPrinted edition: _z9783030165048
776	0	8	_iPrinted edition: _z9783030165055
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-16503-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aPrimersemestre_2019_Engineering
998			_aSI _cm _dz _feng _ggw _h0 _b11/2019 _eu _zSI