Readings in Artificial Intelligence and Databases

The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s.

An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction.

Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.

Acknowledgements
Introduction
Chapter 1 Introduction to AI and Databases
1.1 Database Management: A Survey, by M.L. Brodie and F. Manola
1.2 Knowledge Representation and Reasoning, by H. Levesque
1.3 The Programmer as Navigator. by C.W. Bachman
1.4 Relational Database: A Practical Foundation for Productivity, by E.F. Codd
1.5 Making Believers Out of Computers, by H. Levesque

Chapter 2 Representation and Semantics
2.1 Entity-based Representations
2.1.1 Limitations of Record-Based Information Models, by W. Kent
2.1.2 The Entity-Relationship Model: Towards a Unified View of Data, by P.P.-S. Chen
2.1.3 Using Semantic Networks for Database Management, by N. Roussopoulos and J. Mylopoulos
2.1.4 Databse Abstractions: Aggregation and Generalization, by J.M. Smith and D.C.P. Smith
2.2 Semantic Data Models and Knowledge Representations
2.2.1 A Language Facility for Designing Database-Intensive Applications, by J. Myopoulos, P.A.Bernstein and H.K.T. Wong
2.2.2 The Functional Data Model and the Data Language DAPLEX, by D. Shipman
2.2.3 On the Design and Specification of Database Transactions, by M.L. Brodie and D. Ridjanovic
2.2.3 On the Design and Specification of Database Transactions, by M.L. Brodie and D. Ridjanovic
2.2.4 An Overview of the KL-ONE Knowledge Representation System, by R. Brachman and J. Schmolze
2.3 Logic and Databases
2.3.1 Logic and Databases: A Deductive Approach, by H. Gallaire, J. Minker and J-M. Nicolas
2.3.2 On Closed World Databases, by R. Reiter
2.3.3 Logic for Data Description, by R. Kowalski
2.4 Data/knowledge Base Semantics
2.4.1 Semantics of Databases: The Semantics of Data Models, by H. Biller and E. Neuhold
2.4.2 An Essential Hybrid Reasoning System: Knowledge and Symbol Level Accounts of KRYPTON, by R. Brachman, V. Pigman-Gilbert and H. Levesque
2.4.3 Towards a Logical Reconstruction of Relational Database Theory, by R. Reiter
2.5 Representation Issues:
2.5.1 Knowledge Bases, by H. Levesque
2.5.2 Incomplete Information in a Relational Database, by T. Imielinsky and W. Lipski

Chapter 3 Performance Issues
3.1 Retrieval, Deduction, and Query Processing
3.1.1 A Framework for Choosing a Database Query Language, by M. Jarke and Y. Vassiliou
3.1.2 An Amateur's Introduction to Recursive Query Processing Strategies, by F. Bancilhon and R. Ramakrishnan
3.1.3 Deductive Question-Answering on Relational Data Bases, by R. Reiter
3.1.4 Knowledge Retrieval as Limited Inference, by A.M. Frisch and J.F. Allen
3.2 Data/Knowledge Base Integrity
3.2.1 Fast Maintenance of Integrity Assertions Using Redundant Aggregate Data, by P.A. Bernstein, B. Blaustein and E. Clarke
3.2.2 A sophisticate's Introduction to Database Normalization Theory, by C. Beeri, P.A. Bernstein and N. Goodman
3.2.3 The Programming Language Aspects of ThingLab, a Constraint-Oriented Simulation Laboratory, by A. Borning
3.2.4 Logic for Improving Integrity Checking in Relational Data Bases, by J.-M. Nicolas
3.3 Implementation Techniques
3.3.1 Access Path Selection in a Relational DBMS, by P.G. Selinger, M.M. Astrahan, D.D. Chamberlin, R.A. Lorie and T.G. Price
3.3.2 The Notions of Consistency and Predicate Locks in a Database System, by K.P. Eswaren, J.N. Gray, R. Lorie and I.L. Traiger
3.3.3 Implementation of Integrity Constraints and Views by Query Modification, by M. Stonebraker
3.3.4 Rete: A Fast Algorithm for the Many Pattern/Many Object Pattern Match Problem, by C.L. Forgy
3.4 Data/Knowledge Management Systems
3.4.1 System R: Relational Approach to Database Management, by M.M. Astrahan, M.W. Blasgen, D.D. Chamberlin, E.P. Eswaren, J.N. Gray, P.P. Griffiths, W.F. King, R.A. Lorie, P.R. McJone, J.W. Mehl, G.R. Putzolu, I.L. Traiger, B.W. Wade and V. Watson.
3.4.2 Storage and Access Structures to Support a Semantic Data Model, by A. Chan, S. Danberg, S. Fox, W.K. Lin, A. Nori and D. Ries
3.4.3 A Modular Toolkit For Knowledge Management, by G. Lafue and R. Smith
3.4.4 Inclusion of New Types in Relational Database Systems, by M.R. Stonebraker
3.4.5 On the Evaluation Strategy of EDUCE, by J. Bocca

Epilogue
Future Intelligent Information Systems: AI and Database Technologies Working Together, by M.L. Brodie
Personal Statement: Computer Science and Concern for Our Planet, by Michael L. Brodie
Bibliography
Credits
Index