000			04012nam a22005775i 4500
001			978-3-319-92312-3
003			DE-He213
005			20210201191408.0
007			cr nn 008mamaa
008			180727s2018 gw | s |||| 0|eng d
020			_a9783319923123 _9978-3-319-92312-3
050		4	_aTK5105.5-5105.9
072		7	_aUKN _2bicssc
072		7	_aCOM075000 _2bisacsh
072		7	_aUKN _2thema
082	0	4	_a004.6 _223
100	1		_aOuyang, Ye. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aMining Over Air: Wireless Communication Networks Analytics _h[electronic resource] / _cby Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li.
250			_a1st ed. 2018.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2018.
300			_aXI, 196 p. 72 illus., 51 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
500			_aAcceso multiusuario
505	0		_aWireless Networks -- Artificial Intelligence -- Big Data -- Machine Learning -- Long Term Evolution (LTE) -- The 5th Generation (5G) -- Self-Organizing Networks (SON) -- Quality of Experience (QoE) -- Network Performance -- Data Analytics.
520			_aThis book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireless networks domain. Mining Over Air describes the problems and their solutions for wireless network performance and quality, device quality readiness and returns analytics, wireless resource usage profiling, network traffic anomaly detection, intelligence-based self-organizing networks, telecom marketing, social influence, and other important applications in the telecom industry. Written by authors who study big data analytics in wireless networks and telecommunication markets from both industrial and academic perspectives, the book targets the pain points in telecommunication networks and markets through big data. Designed for both practitioners and researchers, the book explores the intersection between the development of new engineering technology and uses data from the industry to understand consumer behavior. It combines engineering savvy with insights about human behavior. Engineers will understand how the data generated from the technology can be used to understand the consumer behavior and social scientists will get a better understanding of the data generation process.
541			_fUABC ; _cTemporal ; _d01/01/2021-12/31/2023.
650		0	_aComputer communication systems.
650		0	_aData mining.
650		0	_aAlgorithms.
650	1	4	_aComputer Communication Networks. _0https://scigraph.springernature.com/ontologies/product-market-codes/I13022
650	2	4	_aData Mining and Knowledge Discovery. _0https://scigraph.springernature.com/ontologies/product-market-codes/I18030
650	2	4	_aAlgorithm Analysis and Problem Complexity. _0https://scigraph.springernature.com/ontologies/product-market-codes/I16021
700	1		_aHu, Mantian. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aHuet, Alexis. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aLi, Zhongyuan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783319923116
776	0	8	_iPrinted edition: _z9783319923130
776	0	8	_iPrinted edition: _z9783030064037
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-92312-3
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
942			_cLIBRO_ELEC
999			_c242985 _d242984