Ontology Alignment - Bridging the Semantic Gap

von: Marc Ehrig

Springer-Verlag, 2006

ISBN: 9780387365015

Sprache: Englisch

252 Seiten, Download: 14694 KB

Format: PDF, auch als Online-Lesen

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Ontology Alignment - Bridging the Semantic Gap

	Contents	6
	List of Figures	12
	Preface	16
	Introduction and Overview	19
	1.1 Motivation	19
	1.2 Contribution	21
	1.2.1 Problem Outline	21
	1.2.2 Solution Pathway	22
	1.3 Overview	23
	1.3.1 Structure	23
	1.3.2 Reader's Guide	24
	Part I Foundations	26
	Definitions	27
	2.1 Ontology	27
	2.1.1 Ontology Definition	27
	2.1.2 Semantic Web and Web Ontology Language (OWL)	30
	2.1.3 Ontology Example	32
	2.2 Ontology Alignment	35
	2.2.1 Ontology Alignment Definition	35
	2.2.2 Ontology Alignment Representation	36
	2.2.3 Ontology Alignment Example	37
	2.3 Related Terms	39
	2.4 Ontology Similarity	41
	2.4.1 Ontology Similarity Definition	41
	2.4.2 Similarity Layers	42
	2.4.3 Specific Similarity Measures	44
	2.4.4 Similarity in Related Work	50
	2.4.5 Heuristic Definition	50
	Scenarios	52
	3.1 Use Cases	52
	3.1.1 Alignment Discovery	53
	3.1.2 Agent Negotiation / Web Service Composition	53
	3.1.3 Data Integration	54
	3.1.4 Ontology Evolution / Versloning	55
	3.1.5 Ontology Merging	55
	3.1.6 Query and Answer Rewriting / Mapping	56
	3.2 Requirements	57
	Related Work	59
	4.1 Theory of Alignment	59
	4.1.1 Algebraic Approach	59
	4.1.2 Information- Flow- based Approach	60
	4.1.3 Translation Framework	61
	4.2 Existing Alignment Approaches	61
	4.2.1 Classification Guidelines for Alignment Approaches	61
	4.2.2 Ontology Alignment Approaches	63
	4.2.3 Schema Alignment Approaches	67
	4.2.4 Global as View / Local as View	70
	Part II Ontology Alignment Approach	73
	Process	74
	5.1 General Process	74
	5.2 Alignment Approach	77
	5.2.0 Input	77
	5.2.1 Feature Engineering	78
	5.2.2 Search Step Selection	80
	5.2.3 Similarity Computation	81
	5.2.5 Interpretation	85
	5.2.6 Iteration	87
	5.2.7 Output	88
	5.3 Process Description of Related Approaches	89
	5.3.1 PROMPT, Anchor- PROMPT	89
	5.3.2 GLUE	91
	5.3.3 OLA	92
	5.4 Evaluation of Alignment Approach	94
	5.4.1 Evaluation Scenario	94
	5.4.2 Evaluation Measures	95
	5.4.3 Absolute Quality	101
	5.4.4 Data Sets	101
	5.4.5 Strategies	104
	5.4.6 Results	105
	5.4.7 Discussion and Lessons Learned	108
	Advanced Methods	110
	6.1 Efficiency	110
	6.1.1 Challenge	110
	6.1.2 Complexity	111
	6.1.5 Discussion and Lessons Learned	119
	6.2 Machine Learning	120
	6.2.1 Challenge	120
	6.2.2 Machine Learning for Ontology Alignment	121
	6.2.3 Runtime Alignment	126
	6.2.4 Explanatory Component of Decision Trees	127
	6.2.5 Evaluation Scenarios: Training and Test Data Sets	128
	6.2.6 Discussion and Lessons Learned	130
	6.3 Active Alignment	132
	6.3.1 Challenge	132
	6.3.2 Ontology Alignment with User Interaction	133
	6.3.3 Evaluation	134
	6.4 Adaptive Alignment	137
	6.4.1 Challenge	137
	6.4.2 Overview	138
	6.4.3 Create Utility Function	138
	6.4.4 Derive Requirements for Result Dimensions	140
	6.4.5 Derive Parameters	141
	6.4.6 Example	144
	6.4.7 Evaluation	145
	6.4.8 Discussion and Lessons Learned	146
	6.5 Integrated Approach	148
	6.5.1 Integrating the Individual Approaches	148
	6.5.2 Summary of Ontology Alignment Approaches	149
	6.5.3 Evaluation	149
	6.5.4 Discussion and Lessons Learned	151
	Part III Implementation and Application	156
	Tools	157
	7.1 Basic Infrastructure for Ontology Alignment and Mapping - FOAM	157
	7.1.1 User Example	157
	7.1.2 Process Implementation	158
	7.1.3 Underlying Software	159
	7.1.4 Availability and Open Usage	160
	7.1.5 Summary	161
	7.2 Ontology Mapping Based on Axioms	161
	7.2.1 Logics and Inferencing	162
	7.2.2 Formalization of Similarity Rules as Logical Axioms	163
	7.2.3 Evaluation	164
	7.3 Integration into Ontology Engineering Platform	165
	7.3.1 OntoStudio	165
	7.3.2 OntoMap	166
	7.3.3 FOAM in OntoMap	167
	Semantic Web and Peer-to-Peer — SWAP	168
	8.1 Project Description	168
	8.1.1 Core Technologies	169
	8.2 Bibster	170
	8.2.1 Scenario	171
	8.2.2 Design	171
	8.2.3 Ontology Alignment / Duplicate Detection	174
	8.2.4 Application	177
	8.3 Xarop	178
	8.3.1 Scenario	178
	8.3.2 Design	180
	8.3.3 Ontology Alignment	184
	8.3.4 Application	185
	Semantically Enabled Knowledge Technologies - SEKT	186
	9.1 Project Description	186
	9.2 Intelligent Integrated Decision Support for Legal Professionals	188
	9.2.1 Scenario	188
	9.2.2 Use Cases	188
	9.2.3 Design	189
	9.3 Retrieving and Sharing Knowledge in a Digital Library	190
	9.3.1 Scenario	190
	9.3.2 Use Cases	190
	Part IV Towards Next Generation Semantic Alignment	193
	Next Steps	194
	10.1 Generalization	194
	10.1.1 Situation	194
	10.1.2 Generalized Process	195
	10.1.3 Alignment of Petri Nets	196
	10.1.4 Summary	200
	10.2 Complex Alignments	201
	10.2.1 Situation	201
	10.2.2 Types of Complex Alignments	202
	10.2.3 Extended Process for Complex Alignments	203
	10.2.4 Implementation and Discussion	204
	Future	205
	11.1 Outlook	205
	11.2 Limits for Alignment	207
	11.2.1 Errors	207
	11.2.2 Points of Mismatch	208
	11.2.3 Implications	209
	Conclusion	211
	12.1 Content Summary	211
	12.2 Assessment of Contribution	213
	Part V Appendix	217
	A Ontologies	218
	B Complete Evaluation Results	222
	C FOAM Tool Details	228
	References	233
	Index	250

Ontology Alignment - Bridging the Semantic Gap

von: Marc Ehrig

Ontology Alignment - Bridging the Semantic Gap

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