Overview
- Studies the potentials, prospects, and challenges of Big Data Analytics in real-world applications
- Addresses pertinent aspect of the data processing chain
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12072)
Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)
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Table of contents (10 chapters)
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Front Matter
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Methods and Solutions
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Front Matter
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Applications
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Front Matter
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Back Matter
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Knowledge Graphs and Big Data Processing
Editors: Valentina Janev, Damien Graux, Hajira Jabeen, Emanuel Sallinger
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-53199-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2020
Softcover ISBN: 978-3-030-53198-0Published: 16 July 2020
eBook ISBN: 978-3-030-53199-7Published: 15 July 2020
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XI, 209
Number of Illustrations: 7 b/w illustrations, 32 illustrations in colour
Topics: Database Management, Information Systems Applications (incl. Internet), Logic in AI, Computer Appl. in Administrative Data Processing, Business Information Systems