Semantic Web Technologies: Trends and Research in Ontology-based Systems

Description

The Semantic Web combines the descriptive languages RDF (Resource Description Framework) and OWL (Web Ontology Language), with the data-centric, customizable XML (eXtensible Mark-up Language) to provide descriptions of the content of Web documents. These machine-interpretable descriptions allow more intelligent software systems to be written, automating the analysis and exploitation of web-based information.

Software agents will be able to create automatically new services from already published services, with potentially huge implications for models of e-Business.

Semantic Web Technologies provides a comprehensive overview of key semantic knowledge technologies and research.   The authors explain (semi-)automatic ontology generation and metadata extraction in depth, along with ontology management and mediation. Further chapters examine how Semantic Web technology is being applied in knowledge management (“Semantic Information Access”) and in the next generation of Web services.

Semantic Web Technologies:

• Provides a comprehensive exposition of the state-of-the art in Semantic Web research and key technologies.
• Explains the use of ontologies and metadata to achieve machine-interpretability.
• Describes methods for ontology learning and metadata generation.
• Discusses ontology management and evolution, covering ontology change detection and propagation, ontology dependency and mediation.
• Illustrates the theoretical concepts with three case studies on industrial applications in digital libraries, the legal sector and the telecommunication industry.

Graduate and advanced undergraduate students, academic and industrial researchers in the field will all find Semantic Web Technologies an essential guide to the technologies of the Semantic Web.

 

Table of Contents

1. Introduction.

1.1. Semantic Web Technologies.

1.2. The Goal of the Semantic Web.

1.3. Ontologies and Ontology Languages.

1.4. Creating and Managing Ontologies.

1.5. Using Ontologies.

1.6. Applications.

1.7. Developing the Semantic Web.

References.

2. Knowledge Discovery for Ontology Construction.

2.1. Introduction.

2.2. Knowledge Discovery.

2.3. Ontology Definition.

2.4. Methodology for Semi-automatic Ontology Construction.

2.5. Ontology Learning Scenarios.

2.6. Using Knowledge Discovery for Ontology Learning.

2.7. Related Work on Ontology Construction.

2.8. Discussion and Conclusion.

Acknowledgments.

References.

3. Semantic Annotation and Human Language Technology.

3.1. Introduction.

3.2. Information Extraction: A Brief Introduction.

3.3. Semantic Annotation.

3.4. Applying ‘Traditional’ IE in Semantic Web Applications.

3.5. Ontology-based IE.

3.6. Deterministic Ontology Authoring using Controlled Language IE.

3.7. Conclusion.

References.

4. Ontology Evolution.

4.1. Introduction.

4.2. Ontology Evolution: State-of-the-art.

4.3. Logical Architecture.

4.4. Data-driven Ontology Changes.

4.5. Usage-driven Ontology Changes.

4.6. Conclusion.

References.

5. Reasoning With Inconsistent Ontologies: Framework, Prototype, and Experiment.

5.1. Introduction.

5.2. Brief Survey of Approaches to Reasoning with Inconsistency.

5.3. Brief Survey of Causes for Inconsistency in the Semantic WEB.

5.4. Reasoning with Inconsistent Ontologies.

5.5. Selection Functions.

5.6. Strategies for Selection Functions.

5.7. Syntactic Relevance-Based Selection Functions.

5.8. Prototype of Pion.

5.9. Discussion and Conclusions.

Acknowledgment.

References.

6. Ontology Mediation, Merging, and Aligning.

6.1. Introduction.

6.2. Approaches in Ontology Mediation.

6.3. Mapping and Querying Disparate Knowledge Bases.

6.4. Summary.

References.

7. Ontologies for Knowledge Management.

7.1. Introduction.

7.2. Ontology usage Scenario.

7.3. Terminology.

7.4. Ontologies as RDBMS Schema.

7.5. Topic-ontologies versus Schema-ontologies.

7.6. Proton Ontology.

7.7. Conclusion.

References.

8. Semantic Information Access.

8.1. Introduction.

8.2. Knowledge Access and the Semantic WEB.

8.3. Natural Language Generation from Ontologies.

8.4. Device Independence: Information Anywhere.

8.5. SEKTAgent.

8.6. Concluding Remarks.

References.

9. Ontology Engineering Methodologies.

9.1. Introduction.

9.2. The Methodology Focus.

9.3. Past and Current Research.

9.4. Diligent Methodology.

9.5. First Lessons Learned.

9.6. Conclusion and Next Steps.

References.

10. Semantic Web Services—Approaches and Perspectives.

10.1. Semantic Web Services—A Short Overview.

10.2. The WSMO Approach.

10.3. The OWL-S Approach.

10.4. The SWSF Approach.

10.5. The IRS-III Approach.

10.6. The WSDL-S Approach.

10.7. Semantic Web Services Grounding: The Link Between The SWS and Existing Web Services Standards.

10.8. Conclusions and Outlook.

References.

11. Applying Semantic Technology to a Digital Library.

11.1. Introduction.

11.2. Digital Libraries: The State-of-the-art.

11.3. A Case Study: the BT Digital Library.

11.4. The Users’ View.

11.5. Implementing Semantic Technology in a Digital Library.

11.6. Future Directions.

References.

12. Semantic Web: A Legal Case Study.

12.1. Introduction.

12.2. Profile of The Users.

12.3. Ontologies for Legal Knowledge.

12.4. Architecture.

12.5. Conclusions.

References.

13. A Semantic Service Oriented Architecture for the Telecommunications Industry.

13.1. Introduction.

13.2. Introduction to Service Oriented Architectures.

13.3. A Semantic Service Orientated Architecture.

13.4. Semantic Mediation.

13.5. Standards and Ontologies in Telecommunications.

13.6. Case Study.

13.7. Conclusion.

References.

14. Conclusion and Outlook.

14.1. Management of Networked Ontologies.

14.2. Engineering of Networked Ontologies.

14.3. Contextualizing Ontologies.

14.4. Cross Media Resources.

14.5. Social Semantic Desktop.

14.6. Applications.

Author Queries.