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001			86333
003			ES-MaUEC
005			20230207040553.0
007			cr nn 008mamaa
008			160916s2016 gw | s |||| 0|eng d
020			_a9783319445502
024	7		_a10.1007/978-3-319-44550-2 _2doi
040			_aES-MaUEC
050		4	_aQA76.9.B45 _b.F87 2016 EB
082	0	4	_a005.7
100	1		_aFurht, Borko _0Local _999367
245	1	0	_aBig Data Technologies and Applications _cby Borko Furht, Flavio Villanustre
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XVIII, 400 p.) _b118 ilustraciones
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aIntroduction to Big Data -- Big Data Analytics -- Transfer Learning Techniques -- Visualizing Big Data -- Deep Learning and Big Data -- The HPCC/ECL Platform for Big Data -- Scalable Automated Linking Technology for Big Data Computing -- Aggregated Data Analysis in HPCC Systems -- Models for Big Data -- Data Intensive Supercomputing Solutions -- Graph Processing with Massive Datasets: A KEL Primer -- HPCC Systems for Cyber Security Analytics -- Social Network Analytics: Hidden and Complex Fraud Schemes -- Modeling Ebola Spread and Using HPCC/KEL System -- Unsupervised Learning and Image Classification in High Performance Computing Cluster
520			_aThe objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650	0	4	_9495511 _aDatos masivos
650		7	_aBases de datos _0comprobar BNE19900966630 _2embne _9138966
700	1		_aVillanustre, Flavio _999975 _0Local
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-44550-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319445502
907			_a.b12956119 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b09-09-17 _cm _dz _eo _feng _ggw _h0
945			_aQA76.9.B45 .F87 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11598062 _z06-04-17
999			_c86333 _d86333 _x1