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Bisson$bet al.] 210 $aParis$cColin$dc1985 215 $a360 p., 1 c. di tav.$d24 cm 606 $aMAGREB$xGeografia politica e economica$3UONC024795$2FI 620 $aFR$dParis$3UONL002984 676 $a961$cSTORIA DELL'AFRICA SETTENTRIONALE$v21 702 1$aBisson$bJean$3UONV046999 712 $aColin$3UONV249042$4650 801 $aIT$bSOL$c20251114$gRICA 912 $aUON00081246 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI 4 0517 $eSI AA 6979 7 0517 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI VII GEO F C 0024 $eSI SC 15017 5 0024 996 $aMaghreb$9674071 997 $aUNIOR LEADER 05342nam 22006975 450 001 9910254992003321 005 20251116160459.0 010 $a3-540-28608-X 024 7 $a10.1007/978-3-540-28608-0 035 $a(CKB)3710000000765357 035 $a(DE-He213)978-3-540-28608-0 035 $a(MiAaPQ)EBC5594882 035 $a(PPN)194511812 035 $a(EXLCZ)993710000000765357 100 $a20160711d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Stream Management $eProcessing High-Speed Data Streams /$fedited by Minos Garofalakis, Johannes Gehrke, Rajeev Rastogi 205 $a1st ed. 2016. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2016. 215 $a1 online resource (VII, 537 p. 103 illus., 16 illus. in color.) 225 1 $aData-Centric Systems and Applications,$x2197-9723 311 08$a3-540-28607-1 320 $aIncludes bibliographical references. 327 $aPart I: Introduction -- Part II: Computation of Basic Stream Synopses -- Part III: Mining Data Streams -- Part IV: Advanced Topics -- Part V: Systems and Architectures -- Part VI: Applications. . 330 $aWe live in the era of ?Big Data?: Petabytes of digital information are generated daily, and need to be processed and analyzed for interesting patterns and trends. Besides volume, a defining characteristic of Big Data is its velocity; that is, data is instantiated in the form of continuous, high-speed data streams that arrive at rapid rates, and need to be processed and analyzed on a continuous (24x7) basis. Such data streams pose very difficult challenges for conventional data-management architectures, which are built primarily on the concept of persistent, static data collections. This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management. . 410 0$aData-Centric Systems and Applications,$x2197-9723 606 $aDatabase management 606 $aData mining 606 $aBig data 606 $aData structures (Computer science) 606 $aInformation storage and retrieval 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070 606 $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aDatabase management. 615 0$aData mining. 615 0$aBig data. 615 0$aData structures (Computer science) 615 0$aInformation storage and retrieval. 615 14$aDatabase Management. 615 24$aData Mining and Knowledge Discovery. 615 24$aBig Data/Analytics. 615 24$aData Structures. 615 24$aInformation Storage and Retrieval. 676 $a006.7876 702 $aGarofalakis$b Minos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGehrke$b Johannes$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRastogi$b Rajeev$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254992003321 996 $aData Stream Management$92143741 997 $aUNINA