Intelligent Database Systems

Overview

a valuable resource for anyone working on intelligent database systems. Good background coverage of both the field of databases and that of AI are provided in the first part of the book, and later there are some excellent analytical discussions of relevant projects. The authors adopt a very readable style which enables a complex topic to become much more accessible."
- Jenny...
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Overview

a valuable resource for anyone working on intelligent database systems. Good background coverage of both the field of databases and that of AI are provided in the first part of the book, and later there are some excellent analytical discussions of relevant projects. The authors adopt a very readable style which enables a complex topic to become much more accessible."
- Jenny Carter, Department of Computer Science, De Montfort University


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.

Drawing on their extensive experience, the authors evaluate how AI techniques can be integrated with present and future database systems and knowledge based management systems, incorporating AI expertise into system design. The book also addresses the techniques developed recently which are directly used, or are the basis, for data retrieval across the world wide web.

If you are a designer or developer working in the database community, with database and AI products or applications, this book will help you to understand crucial research developments and to apply the results in practice.

Includes:
· Mechanisms for handling data and knowledge including XML, web indexing, search engines & data mining
· Object Oriented Database Management Systems and object-relational DBMS
· Data modeling including techniques suchas Entity Relationship, Functional Data & Semantic Database models, as well as using the notations for modeling (OMT & UML)

Plus! Extended case studies of commercial systems


About the authors:
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.



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Product Details

  • ISBN-13: 9780201877366
  • Publisher: Addison Wesley Professional
  • Publication date: 2/8/2001
  • Series: ACM Press Series
  • Edition number: 1
  • Pages: 352
  • Product dimensions: 7.38 (w) x 9.21 (h) x 0.98 (d)

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.
DATALOGlanguage.
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.
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