Learning OWL class expressions:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Heidelberg
AKA Akademische Verlagesellschaft IOS Press
2010
|
| Schriftenreihe: | Studies on the Semantic Web
v. 006 |
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 Volltext Inhaltsverzeichnis |
| Beschreibung: | Originally presented as: Thesis (doctoral)--Universität Leipzig, 2010 Print version record |
| Beschreibung: | 1 online resource (xiv, 265 pages) illustrations (some color) |
| ISBN: | 1306284775 1607505282 1614993408 389838635X 9781306284776 9781607505280 9781614993407 9783898386357 |
Internformat
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| 100 | 1 | |a Lehmann, Jens |d 1982- |e Verfasser |0 (DE-588)141621273 |4 aut | |
| 245 | 1 | 0 | |a Learning OWL class expressions |c Jens Lehmann |
| 264 | 1 | |a Heidelberg |b AKA Akademische Verlagesellschaft |b IOS Press |c 2010 | |
| 300 | |a 1 online resource (xiv, 265 pages) |b illustrations (some color) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Studies on the Semantic Web |v v. 006 | |
| 500 | |a Originally presented as: Thesis (doctoral)--Universität Leipzig, 2010 | ||
| 500 | |a Print version record | ||
| 650 | 7 | |a COMPUTERS / General |2 bisacsh | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Ontologies (Information retrieval) |2 fast | |
| 650 | 7 | |a Semantic Web |2 fast | |
| 650 | 7 | |a Ontologie <Wissensverarbeitung> |2 swd | |
| 650 | 7 | |a OWL <Informatik> |2 swd | |
| 650 | 7 | |a Terminologische Logik |2 swd | |
| 650 | 7 | |a Maschinelles Lernen |2 swd | |
| 650 | 7 | |a Wissenserwerb |2 swd | |
| 650 | 7 | |a Semantic Web |2 swd | |
| 650 | 4 | |a Ontologies (Information retrieval) | |
| 650 | 4 | |a Semantic Web | |
| 650 | 4 | |a Machine learning | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Lehmann, Jens, 1982- |t Learning OWL class expressions |
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Datensatz im Suchindex
| _version_ | 1804175389655826432 |
|---|---|
| adam_text | CONTENTS
CHAPTER 1. INTRODUCTION 1
1.1 MOTIVATION 1
1.2 CONTRIBUTIONS 4
1.3 CHAPTER OVERVIEW 6
CHAPTER 2. PRELIMINARIES AND STATE OF THE ART 9
2.1 SEMANTIC WEB 9
2.1.1 HISTORY AND VISION 9
2.1.2 RDFANDSPARQL 11
2.1.3 DESCRIPTION LOGICS 14
2.1.4 OWL 23
2.2 CONCEPT LEARNING AND INDUCTIVE REASONING 25
2.2.1 HISTORY, TOOLS, AND APPLICATIONS 28
2.2.2 LEARNING PROBLEMS IN OWL/DLS 33
2.2.3 REFINEMENT OPERATORS IN OWL/DLS 36
CHAPTER 3. THEORETICAL FOUNDATIONS OF REFINEMENT OP-
ERATORS 41
3.1 THE ROLE OF MINIMALITY 42
3.2 COMBINATIONS OF COMPLETENESS, PROPERNESS, FINITENESS,
REDUNDANCY 46
3.3 WEAK COMPLETENESS 55
CHAPTER 4. DESIGNING REFINEMENT OPERATORS 61
4.1 A COMPLETE OWL REFINEMENT OPERATOR 61
4.1.1 DEFINITION OF THE OPERATOR 63
4.1.2 COMPLETENESS OF THE OPERATOR 68
4.1.3 ACHIEVING PROPERNESS 73
4.1.4 CARDINALITY RESTRICTIONS AND CONCRETE ROLE SUP-
PORT 75
XI
BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/1001424875
DIGITALISIERT DURCH
XII CONTENTS
4.1.5 OPTIMISATIONS 78
4.2 AN IDEAL EL REFINEMENT OPERATOR 80
4.2.1 EC, TREES AND SIMULATION RELATIONS 81
4.2.2 FORMAL DESCRIPTION OF THE EL REFINEMENT OP-
ERATOR 87
4.2.3 OPERATOR PERFORMANCE 94
CHAPTER 5. REFINEMENT OPERATOR BASED OWL LEARNING
ALGORITHMS 97
5.1 OCEL (OWL CLASS EXPRESSION LEARNER) 98
5.1.1 REDUNDANCY ELIMINATION 98
5.1.2 CREATING A FULL LEARNING ALGORITHM 99
5.2 ELTL (EL TREE LEARNER) 103
5.3 CELOE (CLASS EXPRESSION LEARNER FOR ONTOLOGY ENGI-
NEERING) 107
CHAPTER 6. IMPROVING SCALABILITY OF OWL LEARNING AL-
GORITHMS 113
6.1 THE DBPEDIA PROJECT 114
6.1.1 THE DBPEDIA KNOWLEDGE EXTRACTION FRAMEWORK 115
6.1.2 THE DBPEDIA KNOWLEDGE BASE 120
6.1.3 INTERLINKED WEB CONTENT 123
6.1.4 APPLICATIONS 126
6.2 KNOWLEDGE FRAGMENT SELECTION 131
6.2.1 WHAT PROPERTIES SHOULD THE FRAGMENT HAVE? 133
6.2.2 EXTENDING CONCISE BOUND DESCRIPTIONS (CBDS) 135
6.2.3 EXTRACTION METHODS 137
6.2.4 OWL DL CONVERSION OF THE FRAGMENT 142
6.2.5 SPARQL IMPLEMENTATION OF TUPLE ACQUISITION 142
6.2.6 USAGE SCENARIOS 143
6.3 OPTIMISING COVERAGE TESTS 148
6.3.1 APPROXIMATE AND PARTIAL CLOSED WORLD REA-
SONING 149
6.3.2 STOCHASTIC COVERAGE COMPUTATION 150
CHAPTER 7. IMPLEMENTATION, EVALUATION, AND USE CASES 155
7.1 THE DL-LEARNER PROJECT 155
7.2 ILP LEARNING PROBLEMS 158
7.2.1 COMPARISON WITH OTHER ALGORITHMS BASED ON
DESCRIPTION LOGICS 159
7.2.2 COMPARISON WITH OTHER ILP APPROACHES 166
CONTENTS XIII
7.3 ONTOLOGY ENGINEERING 170
7.3.1 THE PROTEGE PLUGIN 171
7.3.2 THE ONTOWIKI PLUGIN 174
7.3.3 EVALUATION OF CELOE 176
7.4 FRAGMENT EXTRACTION EVALUATION 180
7.5 FURTHER APPLICATIONS 184
7.5.1 PREDICTIONS OF THE EFFECT OF MUTATIONS ON THE
PROTEIN FUNCTION 184
7.5.2 NLP2RDF 185
7.5.3 ORE - ONTOLOGY REPAIR AND ENRICHMENT 186
7.5.4 MOOSIQUE.NET - MUSIC RECOMMENDATIONS 187
7.6 STRENGTHS AND LIMITATIONS OF THE DESCRIBED APPROACHES 188
CHAPTER 8. RELATED WORK 193
8.1 INDUCTIVE LEARNING IN DESCRIPTION LOGICS 193
8.2 REFINEMENT OPERATORS 196
8.3 (SEMI-)AUTOMATIC ONTOLOGY ENGINEERING 197
8.4 KNOWLEDGE FRAGMENT SELECTION 198
CHAPTER 9. CONCLUSIONS AND FUTURE WORK 201
9.1 REFINEMENT OPERATORS 201
9.2 LEARNING ALGORITHMS AND SCALABILITY 202
9.3 IMPLEMENTATION, EVALUATION AND USE CASES 204
9.4 FUTURE WORK 205
CHAPTER A. SOFTWARE RELEASE HISTORY 209
CHAPTER B. DL-LEARNER MANUAL 211
B.I WHAT IS DL-LEARNER? 211
B.2 GETTING STARTED 213
B.3 DL-LEARNER ARCHITECTURE 214
B.4 DL-LEARNER COMPONENTS 216
B.4.1 KNOWLEDGE SOURCES 216
B.4.2 REASONER COMPONENTS 217
B.4.3 LEARNING PROBLEMS 218
B.4.4 LEARNING ALGORITHMS 219
B.5 DL-LEARNER INTERFACES 222
B.6 EXTENDING DL-LEARNER 223
B.7 GENERAL INFORMATION 225
XIV CONTENTS
CHAPTER C. CURRICULUM VITAE 227
C.I RELATED PEER REVIEWED PUBLICATIONS 228
C.2 OTHER PUBLICATIONS 230
C.3 TALKS 231
C.4 RESEARCH PROJECTS AND GROUPS 232
C.5 PROGRAMM COMMITTEE, REVIEWING 233
C.6 SEMINARS AND TEACHING 233
C.7 SUPERVISION 234
LIST OF TABLES 235
LIST OF FIGURES 237
LIST OF ALGORITHMS 239
LIST OF DEFINITIONS 240
LIST OF THEOREMS 242
LIST OF EXAMPLES AND REMARKS 245
BIBLIOGRAPHY 247
SELBSTAENDIGKEITSERKLAERUNG 264
|
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| dewey-full | 22/GER 006.332 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 022 - Administration of physical plant 006 - Special computer methods |
| dewey-raw | 22/ger 006.332 |
| dewey-search | 22/ger 006.332 |
| dewey-sort | 222 GER |
| dewey-tens | 020 - Library and information sciences 000 - Computer science, information, general works |
| discipline | Informatik Theologie / Religionswissenschaften |
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| language | English |
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| spelling | Lehmann, Jens 1982- Verfasser (DE-588)141621273 aut Learning OWL class expressions Jens Lehmann Heidelberg AKA Akademische Verlagesellschaft IOS Press 2010 1 online resource (xiv, 265 pages) illustrations (some color) txt rdacontent c rdamedia cr rdacarrier Studies on the Semantic Web v. 006 Originally presented as: Thesis (doctoral)--Universität Leipzig, 2010 Print version record COMPUTERS / General bisacsh Machine learning fast Ontologies (Information retrieval) fast Semantic Web fast Ontologie <Wissensverarbeitung> swd OWL <Informatik> swd Terminologische Logik swd Maschinelles Lernen swd Wissenserwerb swd Semantic Web swd Ontologies (Information retrieval) Semantic Web Machine learning Erscheint auch als Druck-Ausgabe Lehmann, Jens, 1982- Learning OWL class expressions http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=683315 Aggregator Volltext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028457056&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Lehmann, Jens 1982- Learning OWL class expressions COMPUTERS / General bisacsh Machine learning fast Ontologies (Information retrieval) fast Semantic Web fast Ontologie <Wissensverarbeitung> swd OWL <Informatik> swd Terminologische Logik swd Maschinelles Lernen swd Wissenserwerb swd Semantic Web swd Ontologies (Information retrieval) Semantic Web Machine learning |
| title | Learning OWL class expressions |
| title_auth | Learning OWL class expressions |
| title_exact_search | Learning OWL class expressions |
| title_full | Learning OWL class expressions Jens Lehmann |
| title_fullStr | Learning OWL class expressions Jens Lehmann |
| title_full_unstemmed | Learning OWL class expressions Jens Lehmann |
| title_short | Learning OWL class expressions |
| title_sort | learning owl class expressions |
| topic | COMPUTERS / General bisacsh Machine learning fast Ontologies (Information retrieval) fast Semantic Web fast Ontologie <Wissensverarbeitung> swd OWL <Informatik> swd Terminologische Logik swd Maschinelles Lernen swd Wissenserwerb swd Semantic Web swd Ontologies (Information retrieval) Semantic Web Machine learning |
| topic_facet | COMPUTERS / General Machine learning Ontologies (Information retrieval) Semantic Web Ontologie <Wissensverarbeitung> OWL <Informatik> Terminologische Logik Maschinelles Lernen Wissenserwerb |
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