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Knowledge Graphs and Big Data Processing

JANEV, Valentina - Personal Name; GRAUX, Damien - Personal Name; JABEEN, Hajira - Personal Name;

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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Detail Information
Series Title
-
Call Number
-
Publisher
Cham : Springer Cham., 2020
Collation
XI, 209
Language
English
ISBN/ISSN
9783030531997
Classification
NONE
Content Type
text
Media Type
computer
Carrier Type
online resource
Edition
1
Subject(s)
Database Management
Specific Detail Info
-
Statement of Responsibility
Valentina Janev, Damien Graux, Hajira Jabeen, Emanuel Sallinger
Other Information
Cataloger
Kholif Basri
Source
-
Validator
-
Digital Object Identifier (DOI)
https://doi.org/10.1007/978-3-030-53199-7
Journal Volume
-
Journal Issue
-
Subtitle
-
Parallel Title
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No other version available

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