One of the main uses of computer systems is the management of large amounts of symbolic information representing the state of some application domain, such as information about all the people I communicate with in my personal address database, or relevant parts of the outer space in the knowledge base of a NASA space mission. While database management systems offer only the basic services of information storage and retrieval, more powerful knowledge systems offer, in addition, a number of advanced services such as deductive and abductive reasoning for the purpose of finding explanations and diagnoses, or generating plans.
In order to design and understand database and knowledge-based applications it is important to build upon well-established conceptual and mathematical foundations. What are the principles behind database and knowledge systems? What are their major components? Which are the important cases of knowledge systems? What are their limitations? Addressing these questions, and discussing the fundamental issues of information update, knowledge assimilation, integrity maintenance, and inference-based query answering, is the purpose of this book.
Foundations of Databases and Knowledge Systems covers both basic and advanced topics. It may be used as the textbook of a course offering a broad introduction to databases and knowledge bases, or it may be used as an additional textbook in a course on databases or Artificial Intelligence. Professionals and researchers interested in learning about new developments will benefit from the encyclopedic character of the book, which provides organized access to many advanced concepts in the theory of databases and knowledge bases.
List of Figures. List of Tables. Preface. Introduction. Part I: Tables and Objects. 1. Conceptual Modeling of Knowledge Bases. 2. Relational Databases. 3. Object-Relational Databases. Part II: Adding Rules. 4. Reaction Rules. 5. Deduction Rules. Part III: Positive Knowledge Systems: Concepts, Properties and Examples. 6. Principles of Positive Knowledge Systems. 7. Temporal Databases. 8. Fuzzy Databases. 9. Further Examples of Positive Knowledge Systems. Part IV: Admitting Negative Information: From Tables to Bitables. 10. Principles of Non-Positive Knowledge Systems. 11. Relational Factbases. 12. Possibilistic Databases. 13. Further Examples of Non-Positive Knowledge Systems. Part V: More on Reaction and Deduction Rules. 14. Communication and Cooperation. 15. Deductive Knowledge Systems. 16. Advanced Knowledge and Reasoning Services. Appendices: A. Partial Logics with Two Kinds of Negation. B. Compositional Possibilistic Logic. C. On the Logic of Temporally Qualified Information. References. Index.
`...recommend the book to all people from database and knowledge communities who want to move their research and practice to more advanced innovative systems.
' Zentralblatt MATH, 910 (1999)
One of the main uses of computer systems is the management of large amounts of symbolic information representing the state of some application domain, such as information about all the people I communicate with in my personal address database, or relevant parts of the outer space in the knowledge base of a NASA space mission. While database management systems offer only the basic services of information storage and retrieval, more powerful knowledge systems offer, in addition, a number of advanced services such as deductive and abductive reasoning for the purpose of finding explanations and diagnoses, or generating plans.
In order to design and understand database and knowledge-based applications it is important to build upon well-established conceptual and mathematical foundations. What are the principles behind database and knowledge systems? What are their major components? Which are the important cases of knowledge systems? What are their limitations? Addressing these questions, and discussing the fundamental issues of information update, knowledge assimilation, integrity maintenance, and inference-based query answering, is the purpose of this book.
Foundations of Databases and Knowledge Systems covers both basic and advanced topics. It may be used as the textbook of a course offering a broad introduction to databases and knowledge bases, or it may be used as an additional textbook in a course on databases or Artificial Intelligence. Professionals and researchers interested in learning about new developments will benefit from the encyclopedic character of the book, which provides organized access to many advanced concepts in the theory of databases and knowledge bases.
1. Conceptual Modeling of Knowledge Bases.- 2. Relational Databases.- 3. Object-Relational Databases.- 4. Reaction Rules.- 5. Deduction Rules.- 6. Principles of Positive Knowledge Systems.- 7. Temporal Databases.- 8. Fuzzy Databases.- 9. Further Examples of Positive Knowledge Systems.- 10. Principles of Non-Positive Knowledge Systems.- 11. Relational Factbases.- 12. Possibilistic Databases.- 13. Further Examples of Non-Positive Knowledge Systems.- 14. Communication and Cooperation.- 15. Deductive Knowledge Systems.- 16. Advanced Knowledge and Reasoning Services.- Appendices.- A- Partial Logics with Two Kinds of Negation.- A.1 Preliminaries.- A.2 Partial Models.- A.3 Classical Logic as a Special Case of Partial Logic.- A.3.1 From Partial to Classical Logic.- A.3.2 Confusing Semi-Partial Logic with Classical Logic.- B- Compositional Possibilistic Logic.- B.1 Introduction.- B.2 Preliminaries.- B.3 The Logical Semantics Problem of Reasoning with Uncertainty.- B.3.1 A Natural Solution.- B.3.2 The Non-Compositional Possibility-Theoretic Approach.- B.4 Semi-Possibilistic Logic.- B.5 Compositional Possibilistic Logic.- C- On the Logic of Temporally Qualified Information.- C.1 Syntax.- C.2 Semantics.- C.3 From Timepoints to Timestamps and Vice Versa.- C.4 Minimal Models.- References.
`...recommend the book to all people from database and knowledge communities who want to move their research and practice to more advanced innovative systems.
' Zentralblatt MATH, 910 (1999)
Inhaltsverzeichnis
List of Figures. List of Tables. Preface. Introduction. Part I: Tables and Objects. 1. Conceptual Modeling of Knowledge Bases. 2. Relational Databases. 3. Object-Relational Databases. Part II: Adding Rules. 4. Reaction Rules. 5. Deduction Rules. Part III: Positive Knowledge Systems: Concepts, Properties and Examples. 6. Principles of Positive Knowledge Systems. 7. Temporal Databases. 8. Fuzzy Databases. 9. Further Examples of Positive Knowledge Systems. Part IV: Admitting Negative Information: From Tables to Bitables. 10. Principles of Non-Positive Knowledge Systems. 11. Relational Factbases. 12. Possibilistic Databases. 13. Further Examples of Non-Positive Knowledge Systems. Part V: More on Reaction and Deduction Rules. 14. Communication and Cooperation. 15. Deductive Knowledge Systems. 16. Advanced Knowledge and Reasoning Services. Appendices: A. Partial Logics with Two Kinds of Negation. B. Compositional Possibilistic Logic. C. On the Logic of Temporally Qualified Information. References. Index.
Klappentext
One of the main uses of computer systems is the management of large amounts of symbolic information representing the state of some application domain, such as information about all the people I communicate with in my personal address database, or relevant parts of the outer space in the knowledge base of a NASA space mission. While database management systems offer only the basic services of information storage and retrieval, more powerful knowledge systems offer, in addition, a number of advanced services such as deductive and abductive reasoning for the purpose of finding explanations and diagnoses, or generating plans. n In order to design and understand database and knowledge-based applications it is important to build upon well-established conceptual and mathematical foundations. What are the principles behind database and knowledge systems? What are their major components? Which are the important cases of knowledge systems? What are their limitations? Addressing these questions, and discussing the fundamental issues of information update, knowledge assimilation, integrity maintenance, and inference-based query answering, is the purpose of this book. n Foundations of Databases and Knowledge Systems covers both basic and advanced topics. It may be used as the textbook of a course offering a broad introduction to databases and knowledge bases, or it may be used as an additional textbook in a course on databases or Artificial Intelligence. Professionals and researchers interested in learning about new developments will benefit from the encyclopedic character of the book, which provides organized access to many advanced concepts in the theory of databases and knowledge bases.
