Entity Resolution and Information Quality

Entity Resolution and Information Quality

1st Edition - December 8, 2010

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  • Author: John Talburt
  • eBook ISBN: 9780123819734
  • Paperback ISBN: 9780123819727

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Description

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.

Key Features

  • First authoritative reference explaining entity resolution and how to use it effectively
  • Provides practical system design advice to help you get a competitive advantage
  • Includes a companion site with synthetic customer data for applicatory exercises, and access to a Java-based Entity Resolution program.

Readership

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.

Table of Contents


  • Foreword

    Preface

    Acknowledgements

    Chapter 1 Principles of Entity Resolution

        Entity Resolution

        Entity Resolution Activities

        Summary

        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

        Summary

        Review Questions

    Chapter 3 Entity Resolution Models

        Overview

        The Fellegi-Sunter Model

        SERF Model

        Algebraic Model

        ENRES Meta-Model

        Summary

        Review Questions

    Chapter 4 Entity-Based Data Integration

        Introduction

        Formal Framework for Describing EBDI

        Optimizing Selection Operator Accuracy

        More Complex Selection Rules

        Summary

        Review Questions

    Chapter 5 Entity Resolution Systems

        Introduction

        DataFlux dfPowerStudio

        Infoglide Identity Resolution Engine

        Acxiom AbiliTec

        Summary

        Review Questions

    Chapter 6 The OYSTER Project

        Background

        OYSTER Logic

        Transitive Equivalence Example

        Asserted Equivalence Example

        Febrl: Open-Source Project

        Summary

        Review Questions

    Chapter 7 Trends in Entity Resolution Research and Applications

        Introduction

        ER and Information Hubs

        Association Analysis and Social Networks

        HPC in ER

        Integration of ER and IQ

        Entity-Based Data Integration

        Fundamental ER Research

        Summary

        Review Questions

    Bibliography

    Glossary

    Appendix

    Index






Product details

  • No. of pages: 256
  • Language: English
  • Copyright: © Morgan Kaufmann 2010
  • Published: December 8, 2010
  • Imprint: Morgan Kaufmann
  • eBook ISBN: 9780123819734
  • Paperback ISBN: 9780123819727

About the Author

John Talburt

Dr. John R. Talburt is Professor of Information Science at the University of Arkansas at Little Rock (UALR) where he is the Coordinator for the Information Quality Graduate Program and the Executive Director of the UALR Center for Advanced Research in Entity Resolution and Information Quality (ERIQ). He is also the Chief Scientist for Black Oak Partners, LLC, an information quality solutions company. Prior to his appointment at UALR he was the leader for research and development and product innovation at Acxiom Corporation, a global leader in information management and customer data integration. Professor Talburt holds several patents related to customer data integration and the author of numerous articles on information quality and entity resolution, and is the author of Entity Resolution and Information Quality (Morgan Kaufmann, 2011). He also holds the IAIDQ Information Quality Certified Professional (IQCP) credential.

Affiliations and Expertise

Professor of Information Science, University of Arkansas at Little Rock, AR, USA

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