Data integration : the relational logic approach /

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Bibliographic Details
Author / Creator:Genesereth, Michael R., 1948-
Imprint:San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, c2010.
Description:1 electronic text (xi, 97 p. : ill.) : digital file.
Language:English
Series:Synthesis lectures on artificial intelligence and machine learning, 1939-4616 ; # 8
Synthesis digital library of engineering and computer science.
Synthesis lectures on artificial intelligence and machine learning, # 8.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/8512869
Hidden Bibliographic Details
ISBN:9781598297423 (electronic bk.)
9781598297416 (pbk.)
Notes:Title from PDF t.p. (viewed on April 7, 2010).
Series from website.
Includes bibliographical references (p. 91-93) and index.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
Also available in print.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Summary:Data integration is a critical problem in our increasingly interconnected but inevitably heterogeneous world. There are numerous data sources available in organizational databases and on public information systems like the World Wide Web. Not surprisingly, the sources often use different vocabularies and different data structures, being created, as they are, by different people, at different times, for different purposes. The goal of data integration is to provide programmatic and human users with integrated access to multiple, heterogeneous data sources, giving each user the illusion of a single, homogeneous database designed for his or her specific need. The good news is that, in many cases, the data integration process can be automated. This book is an introduction to the problem of data integration and a rigorous account of one of the leading approaches to solving this problem, viz., the relational logic approach. Relational logic provides a theoretical framework for discussing data integration. Moreover, in many important cases, it provides algorithms for solving the problem in a computationally practical way. In many respects, relational logic does for data integration what relational algebra did for database theory several decades ago. A companion web site provides interactive demonstrations of the algorithms.
Standard no.:10.2200/S00226ED1V01Y200911AIM008