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Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (6/6)
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Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (6/6)
by Jon Atle Gulla, Vijayan Sugumaran
Applied Semantic Web Technologies
Front Cover
Contents
Acknowledgment
Editors
Contributors (1/2)
Contributors (2/2)
Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (1/4)
Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (2/4)
Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (3/4)
Chapter 1: Applied Semantic Web Technologies: Overview and Future Directions (4/4)
Chapter 2: Ontology: Fundamentals and Languages (1/9)
Chapter 2: Ontology: Fundamentals and Languages (2/9)
Chapter 2: Ontology: Fundamentals and Languages (3/9)
Chapter 2: Ontology: Fundamentals and Languages (4/9)
Chapter 2: Ontology: Fundamentals and Languages (5/9)
Chapter 2: Ontology: Fundamentals and Languages (6/9)
Chapter 2: Ontology: Fundamentals and Languages (7/9)
Chapter 2: Ontology: Fundamentals and Languages (8/9)
Chapter 2: Ontology: Fundamentals and Languages (9/9)
Chapter 3: Toward Semantic Interoperability between Information Systems (1/5)
Chapter 3: Toward Semantic Interoperability between Information Systems (2/5)
Chapter 3: Toward Semantic Interoperability between Information Systems (3/5)
Chapter 3: Toward Semantic Interoperability between Information Systems (4/5)
Chapter 3: Toward Semantic Interoperability between Information Systems (5/5)
Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (1/4)
Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (2/4)
Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (3/4)
Chapter 4: AlViz: A Tool for Ontology Alignment Utilizing Information Visualization Techniques (4/4)
Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (1/4)
Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (2/4)
Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (3/4)
Chapter 5: SRS: A Hybrid Ontology Mediation and Mapping Approach (4/4)
Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (1/6)
Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (2/6)
Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (3/6)
Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (4/6)
Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (5/6)
Chapter 6: An Ontology Engineering Tool for Enterprise 3.0 (6/6)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (1/7)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (2/7)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (3/7)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (4/7)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (5/7)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (6/7)
Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (7/7)
Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (1/6)
Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (2/6)
Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (3/6)
Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (4/6)
Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (5/6)
Chapter 8: Relation Extraction for Semantic Web with Taxonomic Sequential Patterns (6/6)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (1/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (2/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (3/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (4/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (5/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (6/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (7/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (8/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (9/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (10/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (11/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (12/13)
Chapter 9: Data-Driven Evaluation of Ontologies Using Machine Learning Algorithms (13/13)
Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (1/5)
Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (2/5)
Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (3/5)
Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (4/5)
Chapter 10: Automatic Evaluation of Search Ontologies in the Entertainment Domain Using Natural Language Processing (5/5)
Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (1/6)
Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (2/6)
Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (3/6)
Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (4/6)
Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (5/6)
Chapter 11: Adding Semantics to Decision Tables: A New Approach to Data and Knowledge Engineering? (6/6)
Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (1/5)
Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (2/5)
Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (3/5)
Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (4/5)
Chapter 12: Semantic Sentiment Analyses Based on Reputations of Web Information Sources (5/5)
Chapter 13: Semantics and Search (1/7)
Chapter 13: Semantics and Search (2/7)
Chapter 13: Semantics and Search (3/7)
Chapter 13: Semantics and Search (4/7)
Chapter 13: Semantics and Search (5/7)
Chapter 13: Semantics and Search (6/7)
Chapter 13: Semantics and Search (7/7)
Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (1/4)
Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (2/4)
Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (3/4)
Chapter 14: Toward Semantics-Based Service Composition in Transport Logistics (4/4)
Chapter 15: Ontology-Driven Business Process Intelligence (1/7)
Chapter 15: Ontology-Driven Business Process Intelligence (2/7)
Chapter 15: Ontology-Driven Business Process Intelligence (3/7)
Chapter 15: Ontology-Driven Business Process Intelligence (4/7)
Chapter 15: Ontology-Driven Business Process Intelligence (5/7)
Chapter 15: Ontology-Driven Business Process Intelligence (6/7)
Chapter 15: Ontology-Driven Business Process Intelligence (7/7)
Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (1/6)
Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (2/6)
Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (3/6)
Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (4/6)
Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (5/6)
Chapter 16: Semantics for Energy Efficiency in Smart Home Environments (6/6)
Back Cover
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Chapter 7: Learning of Social Ontologies in WWW: Key Issues, Experiences, Lessons Learned, and Future Directions (1/7)
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