Table of contents for Semantic Web technologies : trends and research in ontology-based systems / John Davies, Rudi Studer, Paul Warren.

Bibliographic record and links to related information available from the Library of Congress catalog.

Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


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Contents
1. Introduction 1
1.1. Semantic Web Technologies 1
1.2. The Goal of the Semantic Web 2
1.3. Ontologies and Ontology Languages 4
1.4. Creating and Managing Ontologies 5
1.5. Using Ontologies 6
1.6. Applications 7
1.7. Developing the Semantic Web 8
References 8
2. Knowledge Discovery for Ontology Construction 9
2.1. Introduction 9
2.2. Knowledge Discovery 10
2.3. Ontology Definition 10
2.4. Methodology for Semi-automatic Ontology Construction 11
2.5. Ontology Learning Scenarios 12
2.6. Using Knowledge Discovery for Ontology Learning 13
2.6.1. Unsupervised Learning 14
2.6.2. Semi-supervised, Supervised, and Active Learning 16
2.6.3. Stream Mining and Web Mining 18
2.6.4. Focused Crawling 18
2.6.5. Data Visualization 19
2.7. Related Work on Ontology Construction 22
2.8. Discussion and Conclusion 24
Acknowledgments 24
References 25
3. Semantic Annotation and Human Language Technology 29
3.1. Introduction 29
3.2. Information Extraction: A Brief Introduction 31
3.2.1. Five Types of IE 32
3.2.2. Entities 33
3.2.3. Mentions 33
3.2.4. Descriptions 34
3.2.5. Relations 34
3.2.6. Events 34
3.3. Semantic Annotation 35
3.3.1. What is Ontology-Based Information Extraction 36
3.4. Applying ?Traditional? IE in Semantic Web Applications 37
3.4.1. AeroDAML 38
3.4.2. Amilcare 38
3.4.3. MnM 39
3.4.4. S-Cream 39
3.4.5. Discussion 40
3.5. Ontology-based IE 40
3.5.1. Magpie 40
3.5.2. Pankow 41
3.5.3. SemTag 41
3.5.4. Kim 42
3.5.5. KIM Front-ends 43
3.6. Deterministic Ontology Authoring using Controlled Language IE 45
3.7. Conclusion 48
References 49
4. Ontology Evolution 51
4.1. Introduction 51
4.2. Ontology Evolution: State-of-the-art 52
4.2.1. Change Capturing 53
4.2.2. Change Representation 54
4.2.3. Semantics of Change 56
4.2.4. Change Propagation 58
4.2.5. Change Implementation 59
4.2.6. Change Validation 60
4.3. Logical Architecture 60
4.4. Data-driven Ontology Changes 62
4.4.1. Incremental Ontology Learning 64
4.5. Usage-driven Ontology Changes 66
4.5.1. Usage-driven Hierarchy Pruning 67
4.6. Conclusion 68
References 69
5. Reasoning With Inconsistent Ontologies: Framework, Prototype,
and Experiment 71
5.1. Introduction 71
5.2. Brief Survey of Approaches to Reasoning with Inconsistency 73
5.2.1. Paraconsistent Logics 73
5.2.2. Ontology Diagnosis 74
5.2.3. Belief Revision 74
5.2.4. Synthesis 75
5.3. Brief Survey of Causes for Inconsistency in the Semantic WEB 75
5.3.1. Inconsistency by Mis-representation of Default 75
5.3.2. Inconsistency Caused by Polysemy 77
5.3.3. Inconsistency through Migration from Another Formalism 77
5.3.4. Inconsistency Caused by Multiple Sources 78
5.4. Reasoning with Inconsistent Ontologies 79
5.4.1. Inconsistency Detection 79
5.4.2. Formal Definitions 80
5.5. Selection Functions 82
5.6. Strategies for Selection Functions 83
5.7. Syntactic Relevance-Based Selection Functions 85
5.8. Prototype of Pion 87
5.8.1. Implementation 87
5.8.2. Experiments and Evaluation 88
5.8.3. Future Experiments 91
5.9. Discussion and Conclusions 91
Acknowledgment 92
References 92
6. Ontology Mediation, Merging, and Aligning 95
6.1. Introduction 95
6.2. Approaches in Ontology Mediation 96
6.2.1. Ontology Mismatches 97
6.2.2. Ontology Mapping 97
6.2.3. Ontology Alignment 100
6.2.4. Ontology Merging 102
6.3. Mapping and Querying Disparate Knowledge Bases 104
6.3.1. Mapping Language 106
6.3.2. A (Semi-)Automatic Process for Ontology Alignment 108
6.3.3. OntoMap: an Ontology Mapping Tool 110
6.4. Summary 111
References 112
7. Ontologies for Knowledge Management 115
7.1. Introduction 115
7.2. Ontology usage Scenario 116
7.3. Terminology 117
7.3.1. Data Qualia 119
7.3.2. Sorts of Data 120
7.4. Ontologies as RDBMS Schema 123
7.5. Topic-ontologies versus Schema-ontologies 124
7.6. Proton Ontology 126
7.6.1. Design Rationales 126
7.6.2. Basic Structure 127
7.6.3. Scope, Coverage, Compliance 128
7.6.4. The Architecture of Proton 130
7.6.5. Topics in Proton 131
7.6.6. Proton Knowledge Management Module 133
7.7. Conclusion 135
References 136
8. Semantic Information Access 139
8.1. Introduction 139
8.2. Knowledge Access and the Semantic WEB 139
8.2.1. Limitations of Current Search Technology 140
8.2.2. Role of Semantic Technology 142
8.2.3. Searching XML 143
8.2.4. Searching RDF 144
8.2.5. Exploiting Domain-specific Knowledge 146
8.2.6. Searching for Semantic Web Resources 150
8.2.7. Semantic Browsing 151
8.3. Natural Language Generation from Ontologies 152
8.3.1. Generation from Taxonomies 153
8.3.2. Generation of Interactive Information Sheets 154
8.3.3. Ontology Verbalisers 154
8.3.4. Ontogeneration 154
8.3.5. Ontosum and Miakt Summary Generators 155
8.4. Device Independence: Information Anywhere 156
8.4.1. Issues in Device Independence 157
8.4.2. Device Independence Architectures and Technologies 160
8.4.3. DIWAF 162
8.5. SEKTAgent 164
8.7. Concluding Remarks 166
References 167
9. Ontology Engineering Methodologies 171
9.1. Introduction 171
9.2. The Methodology Focus 172
9.2.1. Definition of Methodology for Ontologies 172
9.2.2. Methodology 173
9.2.3. Documentation 174
9.2.4. Evaluation 174
9.3. Past and Current Research 174
9.3.1. Methodologies 174
9.3.2. Ontology Engineering Tools 177
9.3.3. Discussion and Open Issues 178
9.4. Diligent Methodology 180
9.4.1. Process 180
9.4.2. Argumentation Support 183
9.5. First Lessons Learned 185
9.6. Conclusion and Next Steps 186
References 186
10. Semantic Web Services?Approaches and Perspectives 191
10.1. Semantic Web Services?A Short Overview 191
10.2. The WSMO Approach 192
10.2.1. The Conceptual Model?The Web Services Modeling
Ontology (WSMO) 193
10.2.2. The Language?The Web Service Modeling Language (WSML) 198
10.2.3. The Execution Environment?The Web Service Modeling
Execution Environment (WSMX) 204
10.3. The OWL-S Approach 207
10.3.1. OWL-S Service Profiles 209
10.3.2. OWL-S Service Models 210
10.4. The SWSF Approach 213
10.4.1. The Semantic Web Services Ontology (SWSO) 213
10.4.2. The Semantic Web Services Language (SWSL) 216
10.5. The IRS-III Approach 217
10.5.1. Principles Underlying IRS-III 218
10.5.2. The IRS-III Architecture 220
10.5.3. Extension to WSMO 221
10.6. The WSDL-S Approach 222
10.6.1. Aims and Principles 222
10.6.2. Semantic Annotations 224
10.7. Semantic Web Services Grounding: The Link Between The SWS
and Existing Web Services Standards 226
10.7.1. General Grounding Uses and Issues 226
10.7.2. Data Grounding 228
10.7.3. Behavioral Grounding 230
10.8. Conclusions and Outlook 232
References 234
11. Applying Semantic Technology to a Digital Library 237
11.1. Introduction 237
11.2. Digital Libraries: The State-of-the-art 238
11.2.1. Working Libraries 238
11.2.2. Challenges 239
11.2.3. The Research Environment 241
11.3. A Case Study: the BT Digital Library 242
11.3.1. The Starting Point 242
11.3.2. Enhancing the Library with Semantic Technology 244
11.4. The Users? View 248
11.5. Implementing Semantic Technology in a Digital Library 250
11.5.1. Ontology Engineering 250
11.5.2. BT Digital Library End-user Applications 251
11.5.3. The BT Digital Library Architecture 252
11.5.4. Deployment View of the BT Digital library 255
11.6. Future Directions 255
References 257
12. Semantic Web: A Legal Case Study 259
12.1. Introduction 259
12.2. Profile of The Users 260
12.3. Ontologies for Legal Knowledge 262
12.3.1. Legal Ontologies: State of the Art 263
12.3.2 Ontologies of Professional Knowledge: OPJK 265
12.3.3. Benefits of Semantic Technology And Methodology 267
12.4. Architecture 272
12.4.1. Iuriservice Prototype 272
12.5. Conclusions 278
References 278
13. A Semantic Service Oriented Architecture for the
Telecommunications Industry 281
13.1. Introduction 281
13.2. Introduction to Service Oriented Architectures 282
13.3. A Semantic Service Orientated Architecture 284
13.4. Semantic Mediation 286
13.4.1. Data Mediation 287
13.4.2. Process Mediation 287
13.5. Standards and Ontologies in Telecommunications 287
13.5.1. eTOM 289
13.5.2. SID 289
13.5.3. Adding Semantics 290
13.6. Case Study 290
13.6.1. Broadband Diagnostics 292
13.6.2. The B2B Gateway Architecture 292
13.6.3. Semantic B2B Integration Prototype 294
13.6.4. Prototype Implementation 297
13.7. Conclusion 298
References 299
14. Conclusion and Outlook 301
14.1. Management of Networked Ontologies 301
14.2. Engineering of Networked Ontologies 302
14.3. Contextualizing Ontologies 303
14.4. Cross Media Resources 304
14.5. Social Semantic Desktop 306
14.6. Applications 307

Library of Congress Subject Headings for this publication:

Semantic Web.