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

Details

No. of pages:
256
Language:
English
Copyright:
© 2011
Published:
Imprint:
Morgan Kaufmann
Electronic ISBN:
9780123819734
Print ISBN:
9780123819727

About the author

John R. 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.

Reviews

"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