Information Modelling and Knowledge Bases XVIII 1st Edition by Duzi, Hannu Jaakkola, Kiyoki, Hannu Kangassalo ISBN 1586037102 9781586037109

In the last decades, information modelling and knowledge bases have become hot topics not only in academic communities related to information systems and computer science, but also in business areas where information technology is applied. This book aims to exchange scientific results and experiences achieved in computer science and other related disciplines using innovative methods and progressive approaches. A platform has been established drawing together researchers as well as practitioners dealing with information modelling and knowledge bases. The main topics of this publication target the variety of themes in the domain of information modelling, conceptual analysis, design and specification of information systems, ontologies, software engineering, knowledge and process management, data and knowledge bases. The editors also aim at applying new progressive theories. To this end, much attention is being paid to theoretical disciplines including cognitive science, artificial intelligence, logic, linguistics and analytical philosophy. The selected papers cover many areas of information modelling, namely theory of concepts, database semantics, knowledge representation, software engineering, WWW information management, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, document data management, process management, and many others.

 

Information Modelling and Knowledge Bases XVIII 1st Edition Table of contents:

Part I: Foundations of Information Modelling

2. Basic Concepts in Information Modelling

   • Definition of Information Modelling
   • Types of Information Models: Conceptual, Logical, and Physical Models
   • Information Modelling Methodologies and Frameworks
   • Case Studies in the Application of Information Models
   • Challenges in Information Modelling

3. Ontologies and Semantic Web Technologies

   • Introduction to Ontologies and Their Importance
   • Ontology Representation Languages: OWL, RDF, and SPARQL
   • Building and Managing Ontologies
   • Applications of Ontologies in the Semantic Web
   • Recent Advances in Ontology Engineering

4. Knowledge Representation Techniques

   • Overview of Knowledge Representation (KR)
   • Logic-Based Representation: Propositional and First-Order Logic
   • Frames, Semantic Networks, and Conceptual Graphs
   • Rule-Based Systems and Expert Systems
   • Probabilistic and Fuzzy Knowledge Representation

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Part II: Advanced Information Modelling Techniques

5. Formal Methods in Information Modelling

   • Mathematical Foundations of Information Modelling
   • Formal Specification Languages and Methods
   • Model Checking and Verification in Knowledge Bases
   • Using Formal Methods for Information Consistency
   • Case Studies: Applications of Formal Methods

6. Data Integration and Interoperability

   • Challenges in Data Integration and Harmonization
   • Methods for Data Fusion and Integration
   • Semantic Integration of Heterogeneous Data Sources
   • Interoperability Standards in Knowledge Bases
   • Techniques for Ensuring Data Consistency Across Systems

7. Temporal and Spatial Modelling

   • Modelling Time and Space in Information Systems
   • Temporal Databases and Knowledge Representation
   • Spatial Databases and Geographic Information Systems (GIS)
   • Applications of Temporal and Spatial Modelling in Real-Time Systems
   • Advances in Temporal and Spatial Information Modelling

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Part III: Knowledge Base Construction and Management

8. Building Knowledge Bases

   • Knowledge Acquisition and Representation Techniques
   • Automated Tools for Knowledge Base Construction
   • Methodologies for Knowledge Elicitation
   • Managing Dynamic and Evolving Knowledge Bases
   • Knowledge Base Quality and Maintenance

9. Knowledge Management Systems

   • Fundamentals of Knowledge Management (KM)
   • Strategies for Organizing and Storing Knowledge
   • KM Systems for Collaboration and Decision Making
   • The Role of Knowledge Sharing in Organizations
   • Evaluating the Effectiveness of Knowledge Management Systems

10. Applications of Knowledge Bases

    • Knowledge Bases in Artificial Intelligence (AI) and Expert Systems
    • Decision Support Systems (DSS) and Knowledge-Based Systems (KBS)
    • Knowledge Representation in Natural Language Processing (NLP)
    • Knowledge Bases in Health Informatics and Bioinformatics
    • Knowledge Management in Enterprise Resource Planning (ERP)

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Part IV: Emerging Trends and Future Directions

11. AI, Machine Learning, and Knowledge-Based Systems

    • Integrating Machine Learning with Knowledge Representation
    • Intelligent Agents and Knowledge-Based Learning
    • Hybrid Systems Combining Symbolic and Sub-symbolic Approaches
    • Case Studies in AI and Knowledge-Based Decision Support
    • Future Directions in Knowledge-Driven AI Systems

12. Blockchain, Big Data, and Knowledge Bases

    • The Role of Blockchain Technology in Knowledge Management
    • Big Data Challenges and Their Impact on Knowledge Representation
    • Knowledge Bases in Decentralized Systems and Data Provenance
    • Smart Contracts and Blockchain for Knowledge Sharing
    • Future of Knowledge Management in the Age of Big Data

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Conclusion
13. Concluding Remarks: The Evolution of Information Modelling and Knowledge Bases
– Summary of Key Trends in Information Modelling
– Challenges in Knowledge Representation for Future Systems
– The Growing Importance of Cross-Disciplinary Approaches
– Future Outlook for Knowledge-Based Systems and Applications

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