Entity Resolution and Information Quality book cover

Entity Resolution and Information Quality

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford Entity Resolution Framework, and the Algebraic Model for Entity Resolution, which are the major theoretical models that support Entity Resolution. In relation to this, the book briefly discusses entity-based data integration (EBDI) and its model, which serve as an extension of the Algebraic Model for Entity Resolution. There is also an explanation of how the three commercial ER systems operate and a description of the non-commercial open-source system known as OYSTER. The book concludes by discussing trends in entity resolution research and practice. Students taking IT courses and IT professionals will find this book invaluable.


Database administrators, data/Information analysts, information and enterprise architects, data warehouse and systems engineers, and software developers working on an identity resolution engine or middleware stack.

Paperback, 256 Pages

Published: December 2010

Imprint: Morgan Kaufmann

ISBN: 978-0-12-381972-7


  • "This book is comprehensive, timely, and on the leading edge of the topic. In addition to being comprehensive and systematic, the book has two distinct characteristics: (1) it addresses the issue of entity relationships, which go beyond entity matching. This novel approach generates much richer information about entities; (2) it discusses not only techniques, but also systems that implement the techniques. This system-oriented approach helps the reader to see how to apply the techniques for problem solving."--Dr. Hongwei (Harry) Zhu - Assistant Professor of Information Technology in the College of Business and Public Administration, Old Dominion University

    "Talburt, the author of this book, is one of the organizers of the first graduate degree program in information quality, hosted by the University of Arkansas at Little Rock. The book contains seven easy-to-read chapters. A chapter on trends and research topics in entity resolution closes this short textbook. Some of the suggestions will undoubtedly encourage graduate students to pursue their research on data integration topics. The book offers interesting pointers and bibliographic references for exploring new avenues of research."--Computing Reviews

    "Talburt (information science, U. of Arkansas-Little Rock) presents a textbook developed from a graduate course on the two emerging specialties within information science. Students tend to come from a number of disciplines, so no deep background in information science is assumed, and the material may even be suitable for upper-level undergraduate courses. He covers principles of entity resolution and information quality, entity resolution models and systems, entity-based data integration, the OYSTER open-source software development project, and trends in research and applications."--SciTech Book News


  • Foreword



    Chapter 1 Principles of Entity Resolution

        Entity Resolution

        Entity Resolution Activities


        Review Questions

    Chapter 2 Principles of Information Quality

        Information Quality

        IQ and the Quality of Information

        Two IP Examples

        IQ Management

        Information versus Process

        IQ and HPC

        The Evolution of Information Quality

        IQ as an Academic Discipline

        IQ and ER


        Review Questions

    Chapter 3 Entity Resolution Models


        The Fellegi-Sunter Model

        SERF Model

        Algebraic Model

        ENRES Meta-Model


        Review Questions

    Chapter 4 Entity-Based Data Integration


        Formal Framework for Describing EBDI

        Optimizing Selection Operator Accuracy

        More Complex Selection Rules


        Review Questions

    Chapter 5 Entity Resolution Systems


        DataFlux dfPowerStudio

        Infoglide Identity Resolution Engine

        Acxiom AbiliTec


        Review Questions

    Chapter 6 The OYSTER Project


        OYSTER Logic

        Transitive Equivalence Example

        Asserted Equivalence Example

        Febrl: Open-Source Project


        Review Questions

    Chapter 7 Trends in Entity Resolution Research and Applications


        ER and Information Hubs

        Association Analysis and Social Networks

        HPC in ER

        Integration of ER and IQ

        Entity-Based Data Integration

        Fundamental ER Research


        Review Questions






advert image