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010   $a3-319-44550-2
024 7 $a10.1007/978-3-319-44550-2
035   $a(MiAaPQ)EBC4690714
035   $a(DE-He213)978-3-319-44550-2
035   $a(PPN)195513940
035   $a(EXLCZ)993710000000862115
100   $a20160916d2016      u|             0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aBig Data Technologies and Applications$b[electronic resource] /$fby Borko Furht, Flavio Villanustre
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (xviii, 400 p.) $cill
311   $a3-319-44548-0 
320   $aIncludes bibliographical references at the end of each chapters.
327   $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.
330   $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 SystemsŪ) 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. .
606   $aComputers
606   $aSoftware engineering
606   $aComputer science?Mathematics
606   $aComputer mathematics
606   $aInformation Systems and Communication Service$3https://scigraph.springernature.com/ontologies/product-market-codes/I18008
606   $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029
606   $aMathematical Applications in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/M13110
615  0$aComputers.
615  0$aSoftware engineering.
615  0$aComputer science?Mathematics.
615  0$aComputer mathematics.
615 14$aInformation Systems and Communication Service.
615 24$aSoftware Engineering.
615 24$aMathematical Applications in Computer Science.
676   $a005.7
700   $aFurht$b Borko$4aut$4http://id.loc.gov/vocabulary/relators/aut$0732609
702   $aVillanustre$b Flavio$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254991003321
996   $aBig Data Technologies and Applications$92048312
997   $aUNINA