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Data science techniques for cryptocurrency blockchains

By: Liiv, Innar.
Series: Behaviormetrics: Quantitative Approaches to Human Behavior Service v.9.Publisher: Singapore : Springer, 2021Description: XII, 110 p. ; ill., 25 cm.ISBN: 9789811624179.Subject(s): Blockchains | Databases | Cryptocurrencies | Data mining | Association rule mining | Bipatite graph | Cluster analysis | Decision tree | Edge crossings | Frequentitemsets | Hash identifier | Gephi software | K-means clustering | Network analysis | Off- chain information | Pixelk-oriented visualization | Scikit-learn framework | TransactionentityDDC classification: 005.74 Summary: 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.
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Includes bibliographical references and index.

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.

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