LEADER 04298nam  22007215  450 
001 9910488720903321
005 20250315121218.0
010   $a9789811624186
010   $a9811624186
024 7 $a10.1007/978-981-16-2418-6
035   $a(CKB)5590000000516490
035   $a(MiAaPQ)EBC6665433
035   $a(Au-PeEL)EBL6665433
035   $a(OCoLC)1259591848
035   $a(PPN)269152806
035   $a(DE-He213)978-981-16-2418-6
035   $a(EXLCZ)995590000000516490
100   $a20210623d2021      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aData Science Techniques for Cryptocurrency Blockchains /$fby Innar Liiv
205   $a1st ed. 2021.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2021.
215   $a1 online resource (117 pages)
225 1 $aBehaviormetrics: Quantitative Approaches to Human Behavior,$x2524-4035 ;$v9
311 1 $a9789811624179 
311 1 $a9811624178 
320   $aIncludes bibliographical references and index.
327   $aUnderstanding the Data Model -- Exploration with Structured Query Language -- Association Rules -- Clustering -- Classification -- Visualization -- Network Science -- Conclusions .
330   $aThis book brings together two major trends: data science and blockchains. It is one of the first books to systematically cover the analytics aspects of blockchains, with the goal of linking traditional data mining research communities with novel data sources. Data science and big data technologies can be considered cornerstones of the data-driven digital transformation of organizations and society. The concept of blockchain is predicted to enable and spark transformation on par with that associated with the invention of the Internet. Cryptocurrencies are the first successful use case of highly distributed blockchains, like the world wide web was to the Internet. The book takes the reader through basic data exploration topics, proceeding systematically, method by method, through supervised and unsupervised learning approaches and information visualization techniques, all the way to understanding the blockchain data from the network science perspective. Chapters introduce the cryptocurrency blockchain data model and methods to explore it using structured query language, association rules, clustering, classification, visualization, and network science. Each chapter introduces basic concepts, presents examples with real cryptocurrency blockchain data and offers exercises and questions for further discussion. Such an approach intends to serve as a good starting point for undergraduate and graduate students to learn data science topics using cryptocurrency blockchain examples. It is also aimed at researchers and analysts who already possess good analytical and data skills, but who do not yet have the specific knowledge to tackle analytic questions about blockchain transactions. The readers improve their knowledge about the essential data science techniques in order to turn mere transactional information into social, economic, and business insights.
410  0$aBehaviormetrics: Quantitative Approaches to Human Behavior,$x2524-4035 ;$v9
606   $aStatistics
606   $aMathematical statistics$xData processing
606   $aStatistics
606   $aData mining
606   $aBig data
606   $aApplied Statistics
606   $aStatistics and Computing
606   $aStatistical Theory and Methods
606   $aData Mining and Knowledge Discovery
606   $aBig Data
615  0$aStatistics.
615  0$aMathematical statistics$xData processing.
615  0$aStatistics.
615  0$aData mining.
615  0$aBig data.
615 14$aApplied Statistics.
615 24$aStatistics and Computing.
615 24$aStatistical Theory and Methods.
615 24$aData Mining and Knowledge Discovery.
615 24$aBig Data.
676   $a005.74
700   $aLiiv$b Innar$01072972
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910488720903321
996   $aData Science Techniques for Cryptocurrency Blockchains$92569172
997   $aUNINA