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Data Science Techniques for Cryptocurrency Blockchains
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Catalogue Information
Field name
Details
Dewey Class
519
Title
Data Science Techniques for Cryptocurrency Blockchains ([EBook] /) / by Innar Liiv.
Author
Liiv, Innar
Other name(s)
SpringerLink (Online service)
Edition statement
1st ed. 2021.
Publication
Singapore : : Springer Singapore : : Imprint: Springer, , 2021.
Physical Details
XII, 111 p. 52 illus., 25 illus. in color. : online resource.
Series
Behaviormetrics: Quantitative Approaches to Human Behavior
2524-4035 ; ; 9
ISBN
9789811624186
Summary Note
This 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.:
Contents note
Understanding the Data Model -- Exploration with Structured Query Language -- Association Rules -- Clustering -- Classification -- Visualization -- Network Science -- Conclusions .
Mode of acces to digital resource
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site
https://doi.org/10.1007/978-981-16-2418-6
Links to Related Works
Subject References:
Applied Statistics
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Big Data
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Data mining
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Data Mining and Knowledge Discovery
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Mathematical statistics—Data processing
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Statistical Theory and Methods
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Statistics
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Statistics and Computing
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Authors:
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Liiv, Innar
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Corporate Authors:
SpringerLink (Online service)
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Series:
Behaviormetrics: Quantitative Approaches to Human Behavior
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Classification:
519
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