LEADER 04148nam  22006855  450 
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010   $a981-13-8759-1
024 7 $a10.1007/978-981-13-8759-3
035   $a(CKB)5340000000061504
035   $a(MiAaPQ)EBC5941121
035   $a(DE-He213)978-981-13-8759-3
035   $a(PPN)243770014
035   $a(EXLCZ)995340000000061504
100   $a20190717d2020      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMultimedia Big Data Computing for IoT Applications $eConcepts, Paradigms and Solutions /$fedited by Sudeep Tanwar, Sudhanshu Tyagi, Neeraj Kumar
205   $a1st ed. 2020.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020.
215   $a1 online resource (xiv, 477 pages)
225 1 $aIntelligent Systems Reference Library,$x1868-4394 ;$v163
311   $a981-13-8758-3 
327   $aMultimedia Big data computing for IoT  -- Energy Conservation in MMBD Computing and IoT ? A Challenge -- An Architecture for the Real-Time Data Stream Monitoring in IoT -- Deep learning for Multimedia data in IoT -- Random Forest based Sarcastic Tweet Classification using multiple feature Collection -- Peak Average Power Ratio reduction in FBMC using SLM & PTS techniques -- Intelligent Personality Analysis on Indicators in IoT-MMBD Enabled Environment -- Data Reduction in MMBD Computing -- Large Scale MMBD Management and Retrieval -- Data Reduction Technique for Capsule Endoscopy -- Multimedia Social Big Data: Mining -- Advertisement prediction in social media environment using big data framework.
330   $aThis book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (QoS) requirements, presenting case studies to demonstrate its application. Further, the book examines the layered architecture of MMBD computing and compares the life cycle of both big data and MMBD. Written by leading experts, it also includes numerous solved examples, technical descriptions, scenarios, procedures, and algorithms.
410  0$aIntelligent Systems Reference Library,$x1868-4394 ;$v163
606   $aComputational intelligence
606   $aComputer security
606   $aBig data
606   $aMultimedia information systems
606   $aApplication software
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aSystems and Data Security$3https://scigraph.springernature.com/ontologies/product-market-codes/I28060
606   $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120
606   $aMultimedia Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I18059
606   $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040
615  0$aComputational intelligence.
615  0$aComputer security.
615  0$aBig data.
615  0$aMultimedia information systems.
615  0$aApplication software.
615 14$aComputational Intelligence.
615 24$aSystems and Data Security.
615 24$aBig Data.
615 24$aMultimedia Information Systems.
615 24$aInformation Systems Applications (incl. Internet).
676   $a005.7
702   $aTanwar$b Sudeep$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aTyagi$b Sudhanshu$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aKumar$b Neeraj$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910484861903321
996   $aMultimedia Big Data Computing for IoT Applications$92230338
997   $aUNINA