Cover image for Intelligent database systems
Title:
Intelligent database systems
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Publication Information:
Harlow, Essex : Addison Wesley, 2001
ISBN:
9780201877366

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30000005178946 QA76.9 D3 B48 2001 Open Access Book Book
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Summary

Summary

This book provides a state of the art guide to the new developments in expert database systems, from the unique perspective of both the database and AI areas. It gives complete and detailed coverage of the latest research and practice, including all the need-to-know technical and theoretical approaches in the area.


Author Notes

Elisa Bertino is a well known expert in the integration of AI and database techniques, areas of O-O, distributed, deductive and multimedia databases and database security. She has chaired and given tutorials at many international conferences and published hundreds of journal papers and a book. Elisa is currently a professor of computer science at the University of Milan. Barbara Catania is an assistant professor of computer science at the University of Genova, specializing in deductive and multimedia databases, and indexing techniques in object-oriented and constraint databases. She has presented at a number of international conferences and co-authored a book. Gian Piero Zarri is an internationally renowned consultant and researcher in the areas of knowledge-based systems, natural-language processing, databases and information retrieval systems. He is on the editorial board of a number of international scientific journals and on the program committee of many conferences on Knowledge-Based Systems. Gian Piero currently works as Research Director for CNRS, the French National Centre for Scientific Research.


Table of Contents

1 Introduction
Informal definition of the domain
General characteristics of IDBSs
Data models and the relational data model
A taxonomy of intelligent database systems
Guidelines for using intelligent database systems
2 Efforts originated in a prevailing DB context
Nested and semantic data models
Introduction
The nested relational model
Semantic models
Hyper-semantic data models
Object-oriented approaches to semantic data modeling
Conclusions
Object-oriented database systems
Basic concepts of a core object-oriented data model
Comparison with other data models
Query languages and query processing
Operational aspects
Systems
The ODMG standard
The object-relational data model
Java and databases
Conclusions
Active database systems
Basic concepts
Issues
Architectures
Research relational prototypes--the Starburst Rule System
Commercial relational approaches
3 Efforts originated in prevailing AI context
Characteristics and classification of the knowledge-based systems
Introduction
The resolution principle
Inference by inheritance
Conclusion
Deductive database systems
Basic concepts
DATALOG language
Deductive database systems and logic programming systems--differences
Architectural approaches
Research prototypes
Updates in deductive databases
Integration of deductive database and object database technologies
Constraint databases
Conclusions
Coupling knowledge-based systems (KBSs) with 'standard' database management systems (DBMSs)
Introduction
Architectural solutions
The 'general bridge' solution
Extending a KBS with components proper to a DBMS
The 'tight coupling' approach
Conclusion
Advanced solutions
Introduction
A 'knowledge level' approach to the interaction with an IAS
TELOS, a language for implementing very large 'integral approach' systems
The CYC project
Other projects based on a 'conceptual representation' approach
Lexical approaches to the construction of large KBs
Conclusions
4 The latest developments
Introduction
Temporal databases
Basic concepts
Temporal data models
Temporal query languages
Ontologies
Ontology theoretical foundations
Environments for building ontologies
Structured, semi-structured and unstructured data
Multimedia database
Semi-structured data
Mediators
Motivation
Architecture
Application of mediators to heterogeneous systems
Proposals
Multi-agents systems
Main issues in designing a multi-agent system
Open problems
Internet indexing and retrieval
Basic indexing methods
Search engines or metasearchers
Internet spiders
Data mining
Data mining tasks
Data mining tools
Medical and legal information systems
Medical information systems
Legal information systems
Conclusions
References
Index