Canadian Semantic Web (eBook)

Preface 6
Program Committee 10
Contents 12
Chapter 1 Incremental Query Rewriting with Resolution 18
1.1 Introduction. 18
1.1.1 Settings and motivation. 18
1.1.2 Outline of the proposed method. 21
1.2 Informal method description. 22
1.3 Soundness and completeness of schematic answer computation. 27
1.4 Recording literals as search space pruning constraints. 31
1.5 SQL generation. 33
1.6 Implementation and experiments. 34
1.7 A note on indexing SemanticWeb documents with data abstractions. 37
1.8 Related work. 38
1.9 Summary and future work. 40
References 42
Chapter 2 Knowledge Representation and Reasoning in Norm-Parameterized Fuzzy Description Logics 44
2.1 Introduction 44
2.2 Preliminaries 48
2.3 Fuzzy Set Theory and Fuzzy Logic 49
2.4 Fuzzy Description Logic 51
2.4.1 Syntax of fALCN 52
2.4.2 Semantics of fALCN 52
2.4.3 Knowledge Bases in fALCN 55
2.5 Reasoning Tasks 56
2.6 GCI, NNF, and ABox Augmentation 58
2.7 Reasoning Procedure 60
2.8 Soundness, Completeness, and Termination of the Reasoning Procedure for fALCN 62
2.9 Conclusion and FutureWork 68
References 69
Chapter 3 A Generic Evaluation Model for Semantic Web Services 71
3.1 Introduction 71
3.2 Performance Engineering for Component- and Service-oriented Systems 73
3.3 Requirements for a Generic Evaluation Model 74
3.3.1 Openness 74
3.3.2 Tool Independent 75
3.3.3 Conciseness 75
3.3.4 Preciseness 75
3.3.5 Completeness 75
3.3.6 Based on Classical Problems 76
3.3.7 Different Complexity Levels 76
3.3.8 Common Benchmarking 76
3.3.9 Flexibility to Perform Remote Evaluation 77
3.4 A Generic Evaluation Model for SemanticWeb Services 77
3.4.1 Semantic Web Services Execution Lifecycle 78
3.4.1.1 Service Discovery - S1 78
3.4.1.2 Service Selection - S2 78
3.4.1.3 Service Composition - S3 78
3.4.1.4 Service Mediation - S4 78
3.4.1.5 Service Choreography and Orchestration - S5 79
3.4.1.6 Service Invocation - S6 79
3.4.1.7 External Communication - S7 79
3.4.1.8 Internal Execution Management Time - EM 79
3.4.1.9 Overall Execution Time - T 80
3.4.2 Critical Evaluation Factors 80
3.4.2.1 Response Time - C1 80
3.4.2.2 Resource Consumption - C2 80
3.4.2.3 Resource Availability - C3 81
3.4.2.4 Service Availability - C4 81
3.4.2.5 Meaningfulness of Results - C5 81
3.4.2.6 Correctness of Results - C6 81
3.4.2.7 Completeness of Results - C7 82
3.4.2.8 Consistency of Results - C8 82
3.4.2.9 Degree of Decoupling - C9 82
3.5 Using the Evaluation Model for Semantic Web Services based on TSC 85
3.5.1 Comparing Resource Availability 85
3.5.2 Analyzing Performance on Concurrent Execution of Goals 86
3.5.3 Comparing Communication Overhead 86
3.5.4 Communication Overhead vs. Time Saved in Multiple Goal Execution 86
3.5.5 Comparing Time Taken in Distributed Service Execution 87
3.5.6 Comparing Time Saved by Applications while Executing aGoal 87
3.5.7 Comparing Time Saved in Resource Retrieval by WSMX 88
3.6 RelatedWork 88
3.6.1 Semantic Web Challenge 88
3.6.2 Semantic Web Services Challenge 89
3.6.3 Semantic Service Selection (S3) 89
3.6.4 IEEE Web Services Challenge 89
3.6.5 SEALS Evaluation Campaigns 90
3.6.6 STI International Test Beds and Challenges Service 90
3.6.7 International Rules Challenge at RuleML 91
3.7 Conclusions and FutureWork 91
Acknowledgments. 92
References 92
Chapter 4 A Modular Approach to Scalable Ontology Development 94
4.1 Introduction 94
4.2 Interface-Based Modular Ontologies 97
4.2.1 The Formalism 97
4.2.2 IBF: Scalability and Reasoning Performance 98
4.3 OWL Extension and Tool Support for the Interface-Based Modular Ontology Formalism 98
4.4 Evaluating IBF Modular Ontologies 104
4.4.1 cohesion 104
4.4.2 coupling 106
4.4.3 Knowledge Encapsulation 109
4.5 Case Studies 109
4.5.1 IBF Modular Ontologies 110
4.5.2 IBF Ontologies Analysis 112
4.6 Related Work 114
4.7 Conclusion 115
References 116
4.8 Appendix 118
Chapter 5 Corporate SemanticWeb: Towards the Deployment of Semantic Technologies in Enterprises 119
5.1 Introduction 119
5.2 Application Domains for a Corporate SemanticWeb 120
5.3 Gaps 122
5.4 Corporate SemanticWeb 123
5.5 Corporate Ontology Engineering 125
5.5.1 Modularization and Integration Dimensions of COLM 126
5.5.1.1 Technical Concept 127
5.5.2 Versioning Dimensions of COLM 128
5.5.2.1 Design of the SVoNt Version Control System for OWL Ontologies 129
5.6 Corporate Semantic Collaboration 130
5.6.1 Editor Functionalities 131
5.6.2 User Groups 132
5.6.3 Design of the Light-weight Ontology Editor 133
5.7 Corporate Semantic Search 135
5.7.1 Search in Non-Semantic Data 136
5.7.1.1 Collecting Knowledge with Extreme Tagging Approach 136
5.7.1.2 Preprocessing Texts by Parsing and Chunking 138
5.7.2 Semantic Search Personalization 139
5.7.2.1 Semantic Matchmaking Framework 140
5.8 Conclusion and Outlook 144
References 144
Chapter 6 Semantic Service Matchmaking in the ATM Domain Considering Infrastructure Capability Constraints 146
6.1 Introduction 146
6.2 RelatedWork 149
6.2.1 Technical Integration 149
6.2.2 Semantic Integration with Semantic Web Services 151
6.2.3 Service Matchmaking Approaches 155
6.3 Research Issues 156
6.4 ATM Scenario Description 157
6.5 Semantic Service Matchmaking Approach 160
6.5.1 Identification of Possible Collaboration Candidate Sets 160
6.5.2 Validity-Check and Optimization of Collaborations 162
6.6 Case Study 163
6.6.1 Discussion 164
6.7 Conclusion 166
References 168
Chapter 7 Developing Knowledge Representation in Emergency Medical Assistance by Using Semantic Web Techniques 171
7.1 Introduction 171
7.2 Ontology and Mobile Devices Background 172
7.3 Proposed Approach 174
7.3.1 Ontology Development 175
7.3.1.1 Ontology Modeling 176
7.3.2 Determining the Ontology Domain 176
7.3.3 Enumerating Important Terms, Classes and the Class Hierarchy 177
7.3.4 Defining Properties and Restrictions of Classes 178
7.3.5 Creating Instances and New Terms Extraction 178
7.3.5.1 New Terms Instantiation 180
7.3.6 Semantic Cache 182
7.4 Experimental Environment and Results 183
7.5 Conclusions and FutureWork 183
References 185
Chapter 8 Semantically Enriching the Search System of a Music Digital Library 187
8.1 Introduction 187
8.2 Research Context 189
8.2.1 Previous Work 189
8.2.2 Cantiga Project 189
8.3 MagisterMusicae Search System 190
8.4 Improving Searchability 191
8.4.1 Applying Semantic Web Technologies 191
8.4.1.1 The Domain Ontology 192
8.4.1.2 The Instrument Taxonomy 193
8.4.1.3 The Resources Ontology 195
8.4.1.4 The Concept Taxonomy 195
8.4.2 Linking the Ontology with External Data Sources 197
8.4.2.1 Geographical Enrichment 198
8.4.2.2 Lexical Enrichment 198
8.4.3 Alternative Search Paradigms 199
8.5 Cantiga Semantic Search System 200
8.5.1 Details on the implementation 201
8.6 Evaluation 202
8.7 RelatedWork 204
8.8 Conclusions and FutureWork 205
Acknowledgments 205
References 205
Chapter 9 Application of an Intelligent System Frameworkand the SemanticWeb for the CO2 Capture Process 207
9.1 Introduction 207
9.2 Backgroundt 208
9.2.1 Application Problem Domain 208
9.2.2 Ontology and Semantic Web 208
9.3 Knowledge Modeling and Ontology Construction 209
9.3.1 Ontology Design 209
9.3.2 Ontology Management 211
9.4 Intelligent System Framework 212
9.5 Application of the Semantic Knowledge AWeb-based Expert System 214
9.6 Conclusion and FutureWork 215
Acknowledgments 217
References 217
Chapter 10 Information Pre-Processing using Domain Meta-Ontology and Rule Learning System 218
10.1 Introduction 219
10.2 The domain meta-ontology 221
10.3 The system for semi-automatic population of domain meta-ontology 224
10.4 Details of the Rule Learning System flow 225
References 227