Ontology alignment : bridging the semantic gap

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010139589	TK5105.88815 E37 2007	Open Access Book	Book	Searching... Unknown
Searching... PSZ KL	30000010159663	TK5105.88815 E37 2007	Open Access Book	Book	Searching... Unknown

A large number of information systems use many different individual schemas to represent data. Semantically linking these schemas is a necessary precondition to establish interoperability between agents and services. Consequently, ontology alignment and mapping for data integration has become central to building a world-wide semantic web.

Ontology Alignment: Bridging the Semantic Gap introduces novel methods and approaches for semantic integration. In addition to developing new methods for ontology alignment, the author provides extensive explanations of up-to-date case studies. The topic of this book, coupled with the application-focused methodology, will appeal to professionals from a number of different domains.

Designed for practitioners and researchers in industry, Ontology Alignment: Bridging the Semantic Web Gap is also suitable for advanced-level students in computer science and electrical engineering.

Preface	p. xv
Acknowledgements	p. xvii
1 Introduction and Overview	p. 1
1.1 Motivation	p. 1
1.2 Contribution	p. 3
1.2.1 Problem Outline	p. 3
1.2.2 Solution Pathway	p. 4
1.3 Overview	p. 5
1.3.1 Structure	p. 5
1.3.2 Reader's Guide	p. 6
Part I Foundations
2 Definitions	p. 11
2.1 Ontology	p. 11
2.1.1 Ontology Definition	p. 11
2.1.2 Semantic Web and Web Ontology Language (OWL)	p. 14
2.1.3 Ontology Example	p. 16
2.2 Ontology Alignment	p. 19
2.2.1 Ontology Alignment Definition	p. 19
2.2.2 Ontology Alignment Representation	p. 20
2.2.3 Ontology Alignment Example	p. 21
2.3 Related Terms	p. 23
2.4 Ontology Similarity	p. 25
2.4.1 Ontology Similarity Definition	p. 25
2.4.2 Similarity Layers	p. 26
2.4.3 Specific Similarity Measures	p. 28
2.4.4 Similarity in Related Work	p. 34
2.4.5 Heuristic Definition	p. 34
3 Scenarios	p. 37
3.1 Use Cases	p. 37
3.1.1 Alignment Discovery	p. 38
3.1.2 Agent Negotiation / Web Service Composition	p. 38
3.1.3 Data Integration	p. 39
3.1.4 Ontology Evolution / Versioning	p. 40
3.1.5 Ontology Merging	p. 40
3.1.6 Query and Answer Rewriting / Mapping	p. 41
3.1.7 Reasoning	p. 42
3.2 Requirements	p. 42
4 Related Work	p. 45
4.1 Theory of Alignment	p. 45
4.1.1 Algebraic Approach	p. 45
4.1.2 Information-Flow-based Approach	p. 46
4.1.3 Translation Framework	p. 47
4.2 Existing Alignment Approaches	p. 47
4.2.1 Classification Guidelines for Alignment Approaches	p. 47
4.2.2 Ontology Alignment Approaches	p. 49
4.2.3 Schema Alignment Approaches	p. 53
4.2.4 Global as View / Local as View	p. 56
Part II Ontology Alignment Approach
5 Process	p. 61
5.1 General Process	p. 61
5.2 Alignment Approach	p. 64
5.2.0 Input	p. 64
5.2.1 Feature Engineering	p. 65
5.2.2 Search Step Selection	p. 67
5.2.3 Similarity Computation	p. 68
5.2.4 Similarity Aggregation	p. 69
5.2.5 Interpretation	p. 72
5.2.6 Iteration	p. 74
5.2.7 Output	p. 75
5.3 Process Description of Related Approaches	p. 76
5.3.1 Prompt, Anchor-Prompt	p. 76
5.3.2 Glue	p. 78
5.3.3 Ola	p. 79
5.4 Evaluation of Alignment Approach	p. 81
5.4.1 Evaluation Scenario	p. 81
5.4.2 Evaluation Measures	p. 82
5.4.3 Absolute Quality	p. 88
5.4.4 Data Sets	p. 88
5.4.5 Strategies	p. 91
5.4.6 Results	p. 92
5.4.7 Discussion and Lessons Learned	p. 95
6 Advanced Methods	p. 97
6.1 Efficiency	p. 97
6.1.1 Challenge	p. 97
6.1.2 Complexity	p. 98
6.1.3 An Efficient Approach	p. 100
6.1.4 Evaluation	p. 104
6.1.5 Discussion and Lessons Learned	p. 106
6.2 Machine Learning	p. 107
6.2.1 Challenge	p. 107
6.2.2 Machine Learning for Ontology Alignment	p. 108
6.2.3 Runtime Alignment	p. 113
6.2.4 Explanatory Component of Decision Trees	p. 114
6.2.5 Evaluation	p. 115
6.2.6 Discussion and Lessons Learned	p. 117
6.3 Active Alignment	p. 119
6.3.1 Challenge	p. 119
6.3.2 Ontology Alignment with User Interaction	p. 120
6.3.3 Evaluation	p. 121
6.3.4 Discussion and Lessons Learned	p. 123
6.4 Adaptive Alignment	p. 124
6.4.1 Challenge	p. 124
6.4.2 Overview	p. 125
6.4.3 Create Utility Function	p. 125
6.4.4 Derive Requirements for Result Dimensions	p. 127
6.4.5 Derive Parameters	p. 128
6.4.6 Example	p. 131
6.4.7 Evaluation	p. 132
6.4.8 Discussion and Lessons Learned	p. 133
6.5 Integrated Approach	p. 135
6.5.1 Integrating the Individual Approaches	p. 135
6.5.2 Summary of Ontology Alignment Approaches	p. 136
6.5.3 Evaluation	p. 136
6.5.4 Discussion and Lessons Learned	p. 138
Part III Implementation and Application
7 Tools	p. 145
7.1 Basic Infrastructure for Ontology Alignment and Mapping-Foam	p. 145
7.1.1 User Example	p. 145
7.1.2 Process Implementation	p. 146
7.1.3 Underlying Software	p. 147
7.1.4 Availability and Open Usage	p. 148
7.1.5 Summary	p. 149
7.2 Ontology Mapping Based on Axioms	p. 149
7.2.1 Logics and Inferencing	p. 150
7.2.2 Formalization of Similarity Rules as Logical Axioms	p. 151
7.2.3 Evaluation	p. 152
7.3 Integration into Ontology Engineering Platform	p. 153
7.3.1 OntoStudio	p. 153
7.3.2 OntoMap	p. 154
7.3.3 Foam in OntoMap	p. 155
8 Semantic Web and Peer-to-Peer - SWAP	p. 157
8.1 Project Description	p. 157
8.1.1 Core Technologies	p. 158
8.1.2 Case Studies	p. 159
8.2 Bibster	p. 159
8.2.1 Scenario	p. 160
8.2.2 Design	p. 160
8.2.3 Ontology Alignment / Duplicate Detection	p. 163
8.2.4 Application	p. 166
8.3 Xarop	p. 167
8.3.1 Scenario	p. 167
8.3.2 Design	p. 169
8.3.3 Ontology Alignment	p. 173
8.3.4 Application	p. 174
9 Semantically Enabled Knowledge Technologies - SEKT	p. 175
9.1 Project Description	p. 175
9.1.1 Core Technologies	p. 176
9.1.2 Case Studies	p. 176
9.1.3 Ontology Alignment	p. 176
9.2 Intelligent Integrated Decision Support for Legal Professionals	p. 177
9.2.1 Scenario	p. 177
9.2.2 Use Cases	p. 177
9.2.3 Design	p. 178
9.3 Retrieving and Sharing Knowledge in a Digital Library	p. 179
9.3.1 Scenario	p. 179
9.3.2 Use Cases	p. 179
9.3.3 Design	p. 180
9.4 Heterogeneous Groups in Consulting	p. 180
9.4.1 Scenario	p. 180
9.4.2 Use Cases	p. 180
9.4.3 Design	p. 181
Part IV Towards Next Generation Semantic Alignment
10 Next Steps	p. 185
10.1 Generalization	p. 185
10.1.1 Situation	p. 185
10.1.2 Generalized Process	p. 186
10.1.3 Alignment of Petri Nets	p. 187
10.1.4 Summary	p. 191
10.2 Complex Alignments	p. 192
10.2.1 Situation	p. 192
10.2.2 Types of Complex Alignments	p. 193
10.2.3 Extended Process for Complex Alignments	p. 194
10.2.4 Implementation and Discussion	p. 195
11 Future	p. 197
11.1 Outlook	p. 197
11.2 Limits for Alignment	p. 199
11.2.1 Errors	p. 199
11.2.2 Points of Mismatch	p. 200
11.2.3 Implications	p. 201
12 Conclusion	p. 203
12.1 Content Summary	p. 203
12.2 Assessment of Contribution	p. 205
12.3 Final Statements	p. 207
Part V Appendix
A Ontologies	p. 211
B Complete Evaluation Results	p. 215
C Foam Tool Details	p. 221
C.1 Short description	p. 221
C.2 Download and Installation	p. 221
C.3 Usage	p. 222
C.4 Web Service	p. 222
C.5 Parameters	p. 222
C.6 Additional features of the tool	p. 224
References	p. 227
Index	p. 245

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