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Langue: anglais
Edité par Springer-Nature New York Inc, 2020
ISBN 10 : 3030531988 ISBN 13 : 9783030531980
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Ajouter au panierPaperback. Etat : Brand New. 224 pages. 9.25x6.10x0.87 inches. In Stock.
Langue: anglais
Edité par Electronic Industry Press, 2025
ISBN 10 : 7121492873 ISBN 13 : 9787121492877
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Ajouter au panierpaperback. Etat : New. Language:Chinese.Paperback.Pub Date:2025-01 Publisher:Publishing House of Electronics Industry.
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions.This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
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Ajouter au panierTaschenbuch. Etat : Neu. Knowledge Graphs and Big Data Processing | Valentina Janev (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xi | Englisch | 2020 | Springer | EAN 9783030531980 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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ISBN 10 : 7030814266 ISBN 13 : 9787030814265
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Ajouter au panierHardcover. Etat : New. Language:Chinese.HardCover. Pub Date: 2025-03 Pages: 270 Publisher: Science Press This book explores knowledge graph technology and its innovative applications in financial big data analysis. Addressing the challenges posed by the multidimensional relationships. temporal frequency variations. and peak-and-fat-tail characteristics of financial big data to data analysis. this book proposes a knowledge big graph based on knowledge graphs. This knowledge big graph unifies the organization and rep.
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Langue: anglais
Edité par Springer International Publishing Jul 2020, 2020
ISBN 10 : 3030531988 ISBN 13 : 9783030531980
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions.This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required. 224 pp. Englisch.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 204.
Langue: anglais
Edité par Springer International Publishing, 2020
ISBN 10 : 3030531988 ISBN 13 : 9783030531980
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Open AccessStudies the potentials, prospects, and challenges of Big Data Analytics in real-world applicationsAddresses pertinent aspect of the data processing chainStudies the potenti.
Langue: anglais
Edité par Springer, Springer Jul 2020, 2020
ISBN 10 : 3030531988 ISBN 13 : 9783030531980
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others.The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions.This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 224 pp. Englisch.