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Table of Contents
Foreword; Preface; Contents; Contributors; 1 Enterprise Knowledge Graph: An Introduction; 1.1 A Brief History of Knowledge Graph; 1.1.1 The Arrival of Semantic Networks; 1.1.2 From Semantic Networks to Linked Data; 1.1.3 Knowledge Graphs: An Entity-Centric View of Linked Data; 1.2 Knowledge Graph Technologies in a Nutshell; 1.3 Applications of Knowledge Graphs for Enterprise; 1.4 How to Read This Book; 1.4.1 Structure of This Book; 1.4.2 Who This Book Is For; 1.4.3 How to Use This Book; Part I Knowledge Graph Foundations & Architecture; 2 Knowledge Graph Foundations.
2.1 Knowledge Representation and Query Languages2.1.1 RDF and RDFS; 2.1.2 OWL; 2.1.3 SPARQL; 2.2 Ontologies and Vocabularies; 2.2.1 Some Standard Vocabularies; 2.2.2 schema.org; 2.3 Data Lifting Standards; 2.3.1 RDB2RDF; 2.3.2 GRDDL ; 2.4 Knowledge Graph Versus Linked Data; 2.5 Knowledge Graph for Web Searching and Knowledge Graph for Enterprise; 3 Knowledge Architecture for Organisations; 3.1 Architecture Overview; 3.2 Acquisition and Integration Layer; 3.2.1 Ontology Development; 3.2.2 Ontologisation of Non-Ontological Resources.
3.2.3 Text Integration via Named Entity and Thematic Scope Resolution3.2.4 Ontology Learning; 3.3 Knowledge Storing and Accessing Layer; 3.3.1 Ontology-Based Data Access; 3.3.2 RDF Stores; 3.3.3 Property Graph-Based Stores; 3.3.4 Conclusion: Storing Knowledge Graphs Versus Relational Databases; 3.4 Knowledge Consumption Layer; 3.4.1 Semantic Search; 3.4.2 Summarisation; 3.4.3 Query Generation; 3.4.4 Question Answering; 3.4.5 Conclusion; Part II Constructing, Understanding and Consuming Knowledge Graphs; 4 Construction of Enterprise Knowledge Graphs (I).
4.1 Knowledge Construction and Maintenance Lifecycle4.2 Ontology Authoring: A Competency Question-Driven Approach; 4.2.1 Competency Questions; 4.2.2 Formulation of Competency Questions; 4.2.3 Ontology Authoring Workflow; 4.3 Semi-automated Linking of Enterprise Data for Virtual Knowledge Graphs; 4.3.1 Virtual Knowledge Graph for Knowledge Discovery; 4.3.2 Semantic Tagging and Data Interlinking; 4.3.3 Usage Scenarios; 4.3.4 Conclusion; 5 Construction of Enterprise Knowledge Graphs (II)*; 5.1 Scenario-Driven Named Entity and Thematic Scope Resolution of Unstructured Data*
5.1.1 Framework Description5.1.2 Framework Application Evaluation; 5.2 Open-World Schema Learning for Knowledge Graphs*; 5.2.1 Motivation; 5.2.2 BelNet+; 5.2.3 TBox Learning as Inference; 5.2.4 A Novel Evaluation Framework; 5.2.5 Experiments; 5.2.6 Experimental Results; 5.2.7 Related Work and Summary; 5.2.8 Conclusion; 6 Understanding Knowledge Graphs; 6.1 Understanding Things in KGs: The Summary of Individual Entities; 6.1.1 Entity Data Organisation; 6.1.2 Summarisation of Entity Data; 6.1.3 Conclusion; 6.2 Exploring KGs: The Summary of Entity Description Patterns.
2.1 Knowledge Representation and Query Languages2.1.1 RDF and RDFS; 2.1.2 OWL; 2.1.3 SPARQL; 2.2 Ontologies and Vocabularies; 2.2.1 Some Standard Vocabularies; 2.2.2 schema.org; 2.3 Data Lifting Standards; 2.3.1 RDB2RDF; 2.3.2 GRDDL ; 2.4 Knowledge Graph Versus Linked Data; 2.5 Knowledge Graph for Web Searching and Knowledge Graph for Enterprise; 3 Knowledge Architecture for Organisations; 3.1 Architecture Overview; 3.2 Acquisition and Integration Layer; 3.2.1 Ontology Development; 3.2.2 Ontologisation of Non-Ontological Resources.
3.2.3 Text Integration via Named Entity and Thematic Scope Resolution3.2.4 Ontology Learning; 3.3 Knowledge Storing and Accessing Layer; 3.3.1 Ontology-Based Data Access; 3.3.2 RDF Stores; 3.3.3 Property Graph-Based Stores; 3.3.4 Conclusion: Storing Knowledge Graphs Versus Relational Databases; 3.4 Knowledge Consumption Layer; 3.4.1 Semantic Search; 3.4.2 Summarisation; 3.4.3 Query Generation; 3.4.4 Question Answering; 3.4.5 Conclusion; Part II Constructing, Understanding and Consuming Knowledge Graphs; 4 Construction of Enterprise Knowledge Graphs (I).
4.1 Knowledge Construction and Maintenance Lifecycle4.2 Ontology Authoring: A Competency Question-Driven Approach; 4.2.1 Competency Questions; 4.2.2 Formulation of Competency Questions; 4.2.3 Ontology Authoring Workflow; 4.3 Semi-automated Linking of Enterprise Data for Virtual Knowledge Graphs; 4.3.1 Virtual Knowledge Graph for Knowledge Discovery; 4.3.2 Semantic Tagging and Data Interlinking; 4.3.3 Usage Scenarios; 4.3.4 Conclusion; 5 Construction of Enterprise Knowledge Graphs (II)*; 5.1 Scenario-Driven Named Entity and Thematic Scope Resolution of Unstructured Data*
5.1.1 Framework Description5.1.2 Framework Application Evaluation; 5.2 Open-World Schema Learning for Knowledge Graphs*; 5.2.1 Motivation; 5.2.2 BelNet+; 5.2.3 TBox Learning as Inference; 5.2.4 A Novel Evaluation Framework; 5.2.5 Experiments; 5.2.6 Experimental Results; 5.2.7 Related Work and Summary; 5.2.8 Conclusion; 6 Understanding Knowledge Graphs; 6.1 Understanding Things in KGs: The Summary of Individual Entities; 6.1.1 Entity Data Organisation; 6.1.2 Summarisation of Entity Data; 6.1.3 Conclusion; 6.2 Exploring KGs: The Summary of Entity Description Patterns.