Semantic Web (eBook)

Implications for Technologies and Business Practices

Michael Workman (Herausgeber)

eBook Download: PDF

2015 | 1st ed. 2016
X, 229 Seiten
Springer International Publishing (Verlag)
978-3-319-16658-2 (ISBN)

Infos

This book examines recent developments in semantic systems that can respond to situations and environments and events. The contributors to this book cover how to design, implement and utilize disruptive technologies. The editor discusses the two fundamental sets of disruptive technologies: the development of semantic technologies including description logics, ontologies and agent frameworks; and the development of semantic information rendering and graphical forms of displays of high-density time-sensitive data to improve situational awareness. Beyond practical illustrations of emerging technologies, the editor proposes to utilize an incremental development method called knowledge scaffolding -a proven educational psychology technique for learning a subject matter thoroughly. The goal of this book is to help readers learn about managing information resources, from the ground up and reinforcing the learning as they read on.

Michael D. Workman, Ph.D. is a Professor of Computer Information Systems and Human Factors with the College of Engineering, School of Computing at the Florida Institute of Technology.

Inhalt

Preface 5
Contents 7
Contributors 9
Chapter-1 11
Introduction to This Book 11
1.1 Resource Description Framework 11
1.2 Ontology Markup 13
1.3 Agent Frameworks 14
1.4 Looking Forward 15
References 15
Chapter-2 16
Semantic Cognition and the Ontological to Epistemic Transformation: Using Technologies to Facilitate Understanding 16
2.1 Introduction 16
Structure, Structuration, and Agency 16
Agency and Agent Systems 18
Goal-Directed Agents 19
The Problem of Meaning 20
2.2 Cognition Overview 21
Memory and Cognition 21
Information Structure and Semantics 23
2.3 Visual Perception 25
Vision and Visual Perception 25
Visual Memory Processing 26
2.4 Memory and Attention 27
Working Memory 28
Types of Memory 29
Cognitive Processing 30
Semantic Relatedness and Cognition 33
Semantic Priming 34
Content and Technical Accuracy 35
2.5 Summary 36
References 36
Chapter-3 40
Using Symbols for Semantic Representations: A Pilot Study of Clinician Opinions of a Web 3.0 Medical Application 40
3.1 Introduction 40
3.2 Theory Foundations and Design Principles 41
3.3 Method 43
Participants and Preparations 43
Instrumentation 44
Procedures 45
3.4 Results 45
3.5 Discussion 46
References 47
Chapter-4 48
Emerging Semantic-Based Applications 48
4.1 Background 50
4.2 Semantics Behind Keywords 53
Semantic Keyword-Based Search: QueryGen 54
Semantic Data Retrieval: Doctopush 60
4.3 Semantic Information Extraction: GENIE 63
4.4 Technologies for Fuzzy Knowledge 67
Modeling Fuzzy Ontologies with Fuzzy OWL 2 70
Reasoning with Fuzzy Ontologies Using fuzzyDL 72
Reasoning with Fuzzy Ontologies Using DeLorean 73
4.5 Applying Semantic Web Technologies to Mobile Computing 74
Semantic Location Granules 75
Semantic Management of LBSs: SHERLOCK 80
4.6 Discussion 85
References 87
Chapter-5 93
Semantics: Revolutionary Breakthrough or Just Another Way of Doing Things? 93
5.1 Introduction 93
The Data World Today: Relational Plus 94
What Would be Better? And by what Criteria? 96
What We Mean by Semantic Technology? 97
Foundational Concepts in Modeling 99
Importance of Similarity 102
Importance of Model Theory 102
Logic and Logic Programming as Reference 103
RDF, RDFS, and OWL as Semantic Languages 104
Evaluation of Semantic Web Languages Against Criteria 107
5.2 How Are Semantic Web Languages Different? 108
Comparison with and Evaluation of XML 108
Comparison and Evaluation of Object-Oriented Languages 110
Relational Revisited: Comparison and Evaluation 112
Comparison and Evaluation of UML with Notes on MOF, eMOF, ODM, and SMOF 116
Summary of Representations 118
5.3 Semantics in Real-World Solutions 119
Model-Driven Equipment Overhaul: Common Understanding 119
Data Provenance: Information Availability 120
Early Manufacturability: Inference 121
Smart Grid: Interoperability 122
Data Science: Data Speaks 123
5.4 Conclusion 124
References 124
Chapter-6 127
Unnatural Language Processing: Characterizing the Challenges in Translating Natural Language Semantics into Ontology Semantics 127
6.1 Introduction 127
6.2 Levels of NL Semantics 129
6.3 Morphological Level 129
6.4 Lexical Level 134
6.5 Syntax-Level 139
6.6 Summary and Value Proposition 141
References 142
Chapter-7 144
The Lexical Bridge: A Methodology for Bridging the Semantic Gaps Between a Natural Language and an Ontology 144
7.1 Introduction 144
7.2 Technical Approach: The LB 145
Lexicalized Ontology Example 145
LB Components 146
Building the LB 147
Potential Applications of the LB 148
RDF Redundancy Definition 149
LB Methodology Applied to RDF Redundancy Evaluation 150
LB Architecture 152
LB Prototype and Results 153
7.3 Conclusion and Next Steps 157
References 158
Chapter-8 159
Reliable Semantic Systems for Decision Making: Defining a Business Rules Ontology for a Survey Decision System 159
8.1 Structure of Researched Data 159
8.2 Applying Semantic Technologies to a Survey Decision Support System 162
Analysis of Questions and Responses 162
Analysis of Secondary Data and Business Rules 164
Requirements and Data Analysis Techniques 165
Decision Support Systems 166
Requirements Engineering 167
Visual Data Analysis 169
Business Rules Analysis 171
Semantic Analysis 172
8.3 Pattern Analysis and Validation Techniques 172
8.4 Architecture of a Semantic Decision Domain 174
8.5 Conclusion 176
References 177
Chapter-9 179
University Ontology: A Case Study at Ahlia University 179
9.1 Introduction 179
9.2 University Ontology 180
Building the Ontology 180
Specification 181
Property and Relationship 182
Implementation 184
Verification 184
9.3 Case: Ahlia University Ontology 185
Conclusion 188
References 189
Chapter-10 190
Semantic Enrichment of Event Stream for Semantic Situation Awareness 190
10.1 Introduction 190
10.2 Overview on Event Processing 191
Finite-State Machine 192
Graph-Based Approaches 193
Rule-Based Approaches 193
RETE Algorithm in Event Processing 194
Storage-Based Event Processing 195
Data Stream Processing Systems 196
10.3 Semantic Complex Event Processing 197
Issues and Challenges 198
Applications of Knowledge-Based Event Processing 201
Example Use Case: High-Level Market Monitoring 201
Approaches for Knowledge-Based Event Processing 204
Stream Reasoning and Resource Description Framework Processing Systems 205
10.4 Fusion of Event Stream and Knowledge 206
Semantic Enrichment 209
Plan-Based Semantic Enrichment 210
Planning Multistep Event Enrichment and Detection 212
10.5 Summary and Discussion 212
References 213
Chapter-11 218
Semantic Web and Business: Reaching a Tipping Point? 218
11.1 Placing the Web in Context 218
A Review of Traditional Semantic Technology Application to Business 220
Historical Understanding of Business Applications Tied to the Semantic Web 222
Data Annotation 223
Search 224
Social Media Analysis 224
Knowledge Management 224
Data Integration 225
Semantic Web Technologies are Not Keeping Up 225
Trends that Could Tip the Scale 226
Larger and Larger Shopper Profiles 227
Omni-channel Marketing 228
Personalization 229
Real-Time and Contextual Communication 229
The Future of Semantic Technologies and Today’s Marketing Challenge 230
Ontology Extraction 231
Personal Ontology Development 231
Personal Ontology Fusion 231
Reasoning and Simulation for Consumer 232
Agent-Based Frameworks 232
11.2 Conclusions 233
References 233

Produkt-Details

• Erscheint lt. Verlag: 27.8.2015
• Zusatzinfo: X, 229 p. 45 illus., 20 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Logistik / Produktion
• Schlagworte: Information and Organization • New Information Resource Management • Semantic Systems • semantic web • Web 3.0
• ISBN-10: 3-319-16658-1 / 3319166581
• ISBN-13: 978-3-319-16658-2 / 9783319166582