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Book
Knowledge Graphs and Big Data Processing
Authors: --- --- --- ---
ISBN: 3030531996 3030531988 Year: 2020 Publisher: Springer Nature

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Abstract

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.

Keywords

Database management. --- Application software. --- Artificial intelligence. --- Computer logic. --- Management information systems. --- Database Management. --- Information Systems Applications (incl. Internet). --- Logic in AI. --- Computer Appl. in Administrative Data Processing. --- Business Information Systems. --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Computer science logic --- Logic, Symbolic and mathematical --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Communication systems --- Database Management --- Information Systems Applications (incl. Internet) --- Logic in AI --- Computer Appl. in Administrative Data Processing --- Business Information Systems --- Computer and Information Systems Applications --- Computer Application in Administrative Data Processing --- artificial intelligence --- big data --- data analytics --- data handling --- data integration --- data mining --- databases --- digital storage --- domain knowledge --- graph theory --- information management --- information technology --- integrated data --- internet --- knowledge management --- knowledge-based system --- ontologies --- semantics --- Databases --- Database programming --- Information retrieval --- Internet searching --- Artificial intelligence --- Public administration --- Information technology: general issues --- Business mathematics & systems


Book
Knowledge Graphs and Big Data Processing
Authors: --- --- --- ---
ISBN: 9783030531997 3030531996 Year: 2020 Publisher: Springer Nature

Loading...
Export citation

Choose an application

Bookmark

Abstract

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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