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Semantic Web Technologies for Intelligent Engineering Applications

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Cover of 'Semantic Web Technologies for Intelligent Engineering Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Multi-Disciplinary Engineering for Industrie 4.0: Semantic Challenges and Needs
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    Chapter 3 An Introduction to Semantic Web Technologies
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    Chapter 4 The Engineering Knowledge Base Approach
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    Chapter 5 Semantic Modelling and Acquisition of Engineering Knowledge
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    Chapter 6 Semantic Matching of Engineering Data Structures
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    Chapter 7 Knowledge Change Management and Analysis in Engineering
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    Chapter 8 Semantic Data Integration: Tools and Architectures
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    Chapter 9 Product Ramp-up for Semiconductor Manufacturing Automated Recommendation of Control System Setup
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    Chapter 10 Ontology-Based Simulation Design and Integration
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    Chapter 11 Semantic Web Solutions in Engineering
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    Chapter 12 Semantic Web Solutions in the Automotive Industry
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    Chapter 13 Leveraging Semantic Web Technologies for Consistency Management in Multi-viewpoint Systems Engineering
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    Chapter 14 Applications of Semantic Web Technologies for the Engineering of Automated Production Systems—Three Use Cases
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    Chapter 15 Conclusions and Outlook
Attention for Chapter 2: Multi-Disciplinary Engineering for Industrie 4.0: Semantic Challenges and Needs
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