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.

描述

語義網絡結合了描述性語言RDF（資源描述框架）和OWL（Web本體語言），以及以數據為中心、可定制的XML（可擴展標記語言），提供Web文檔內容的描述。這些可由機器解讀的描述使得更智能的軟件系統能夠自動化分析和利用基於Web的信息。

軟件代理將能夠從已發布的服務中自動創建新服務，對電子商務模型可能產生巨大的影響。

《語義網絡技術》提供了關鍵語義知識技術和研究的全面概述。作者深入解釋了（半）自動本體生成和元數據提取，以及本體管理和調解。更多章節探討了語義網絡技術在知識管理（“語義信息訪問”）和下一代Web服務中的應用。

《語義網絡技術》：

- 提供了語義網絡研究和關鍵技術的全面介紹。
- 解釋了使用本體和元數據實現機器可解釋性。
- 描述了本體學習和元數據生成的方法。
- 討論了本體管理和演進，包括本體變化檢測和傳播，本體依賴性和調解。
- 通過在數字圖書館、法律部門和電信行業的工業應用案例中舉例說明了理論概念。

研究生和高年級本科生，以及該領域的學術和工業研究人員都會發現《語義網絡技術》是語義網絡技術的必備指南。

目錄

1. 簡介。
1.1. 語義網絡技術。
1.2. 語義網絡的目標。
1.3. 本體和本體語言。
1.4. 創建和管理本體。
1.5. 使用本體。
1.6. 應用。
1.7. 發展語義網絡。
參考文獻。
2. 本體構建的知識發現。
2.1. 簡介。
2.2. 知識發現。
2.3. 本體定義。
2.4. 半自動本體構建方法。
2.5. 本體學習場景。
2.6. 使用知識發現進行本體學習。