Fensel / Simsek / Angele Knowledge Graphs

Methodology, Tools and Selected Use Cases
1. Auflage 2020
ISBN: 978-3-030-37439-6
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 156 Seiten

This book describes methods and tools that empower information providers to build and maintain knowledge graphs, including those for manual, semi-automatic, and automatic construction; implementation; and validation and verification of semantic annotations and their integration into knowledge graphs. It also presents lifecycle-based approaches for semi-automatic and automatic curation of these graphs, such as approaches for assessment, error correction, and enrichment of knowledge graphs with other static and dynamic resources.
Chapter 1 defines knowledge graphs, focusing on the impact of various approaches rather than mathematical precision. Chapter 2 details how knowledge graphs are built, implemented, maintained, and deployed. Chapter 3 then introduces relevant application layers that can be built on top of such knowledge graphs, and explains how inference can be used to define views on such graphs, making it a useful resource for open and service-oriented dialog systems. Chapter 4 discusses applications of knowledge graph technologies for e-tourism and use cases for other verticals. Lastly, Chapter 5 provides a summary and sketches directions for future work. The additional appendix introduces an abstract syntax and semantics for domain specifications that are used to adapt schema.org to specific domains and tasks.
To illustrate the practical use of the approaches presented, the book discusses several pilots with a focus on conversational interfaces, describing how to exploit knowledge graphs for e-marketing and e-commerce. It is intended for advanced professionals and researchers requiring a brief introduction to knowledge graphs and their implementation. 
                 

       
          

Dieter Fensel is the director of the STI Innsbruck research group at the University of Innsbruck's Department of Computer Science. He has written over 300 scientific publications, including books, journals and conference papers, and workshop contributions. As one of the pioneers of research in the Semantic Web, he co-founded major scientific events such as the Extended Semantic Web Conference (ESWC) and the International Semantic Web Conference (ISWC). His research interests currently focus on the development of knowledge graphs and various aspects of the knowledge graph lifecycle. He has successfully applied his research in industry by co-founding companies like seekda (now part of Kognitiv) and Onlim, which are active in conversational interfaces and knowledge graphs. The book has been co-authored under his guidance, by his team of researchers at STI Innsbruck (Kevin Angele, Elwin Huaman, Elias Kärle, Oleksandra Panasiuk and Umutcan ?im?ek) and Onlim GmbH (Alexander Wahler, Jürgen Umbrich and Ioan Toma).

        

Autoren/Hrsg.

Fensel, Dieter

Simsek, Umutcan

Angele, Kevin

Huaman, Elwin

Kärle, Elias

Panasiuk, Oleksandra

Toma, Ioan

To, Ioan

Umbrich, Jürgen

Wahler, Alexander

Inhaltsverzeichnis

1;Foreword;5
2;Preface;8
3;Acknowledgment;11
4;Contents;12
5;Chapter 1: Introduction: What Is a Knowledge Graph?;14
5.1;1.1 Introduction;14
5.2;1.2 A Conceptual Definition of Knowledge Graphs;15
5.3;1.3 An Empirical Definition of Knowledge Graphs;19
5.3.1;1.3.1 Open Knowledge Graphs;19
5.3.2;1.3.2 Proprietary Knowledge Graphs;22
6;Chapter 2: How to Build a Knowledge Graph;24
6.1;2.1 Introduction;24
6.2;2.2 Knowledge Creation;26
6.2.1;2.2.1 Knowledge Creation Methodology;27
6.2.2;2.2.2 Our Modelling Language;28
6.2.3;2.2.3 Knowledge Generation Tools;33
6.2.3.1;2.2.3.1 Manual Editing;33
6.2.3.2;2.2.3.2 Semi-automatic Editing;36
6.2.3.3;2.2.3.3 Mapping;36
6.2.3.4;2.2.3.4 Automatic Annotation Tools;37
6.2.3.5;2.2.3.5 Evaluation;41
6.3;2.3 Knowledge Hosting;44
6.3.1;2.3.1 Collection, Storage, and Retrieval of Semantic Annotations;45
6.3.2;2.3.2 Collection, Storage, and Retrieval of Knowledge Graphs;47
6.4;2.4 Knowledge Curation;48
6.4.1;2.4.1 A Maximal Simple Knowledge Representation Formalism;49
6.4.2;2.4.2 Knowledge Assessment;50
6.4.2.1;2.4.2.1 Literature;50
6.4.2.2;2.4.2.2 Task Types;55
6.4.2.3;2.4.2.3 Methods and Tools;56
6.4.3;2.4.3 Knowledge Cleaning;59
6.4.3.1;2.4.3.1 Literature;60
6.4.3.2;2.4.3.2 Task Types;60
6.4.3.3;2.4.3.3 Methods and Tools;62
6.4.3.4;2.4.3.4 Summary;64
6.4.4;2.4.4 Knowledge Enrichment;65
6.4.4.1;2.4.4.1 Literature;66
6.4.4.2;2.4.4.2 Task Types;68
6.4.4.3;2.4.4.3 Methods and Tools;68
6.4.4.4;2.4.4.4 Summary;74
6.4.5;2.4.5 Summary on Knowledge Curation;74
6.5;2.5 Knowledge Deployment: The Use of the Pudding Is in the Eating;75
7;Chapter 3: How to Use a Knowledge Graph;82
7.1;3.1 Introduction;82
7.2;3.2 Merging Artificial Intelligence and the Internet;83
7.2.1;3.2.1 60 Years of AI in a Glimpse;83
7.2.2;3.2.2 The Web (for Bots);84
7.2.3;3.2.3 Summary;91
7.3;3.3 Knowledge Access Layer;91
7.3.1;3.3.1 Loosely Connected TBoxes Defining Logic-Based Views on Knowledge Graphs;92
7.3.2;3.3.2 Dynamic and Active Data: Semantic Web Services;96
7.4;3.4 Open and Service-Oriented Dialog Systems;98
7.4.1;3.4.1 Open Dialog Systems;98
7.4.2;3.4.2 Service-Guided Dialogs;104
7.4.3;3.4.3 Summary;105
8;Chapter 4: Why We Need Knowledge Graphs: Applications;107
8.1;4.1 Introduction;107
8.2;4.2 The Market;108
8.3;4.3 Motivation and Solution;109
8.4;4.4 Touristic Use Cases;113
8.5;4.5 Energy Use Cases;119
8.6;4.6 Further Verticals;122
8.7;4.7 Summary;123
9;Chapter 5: Conclusions;125
10;Appendix;128
10.1;A.1 Abstract Syntax and Semantics of Domain Specifications;128
10.1.1;A.1.1 SHACL (As We Adopt);129
10.1.2;A.1.2 Conceptual Description of Domain Specification;130
10.1.2.1;A.1.2.1 Simple Domain Specification (SDS);130
10.1.2.2;A.1.2.2 Restriction Domain Specification;131
10.1.2.3;A.1.2.3 Extension Domain Specification;131
10.1.3;A.1.3 Abstract Syntax;131
10.1.4;A.1.4 Semantics;137
11;References;139
12;Index;154