
Entity Resolution and Information Quality
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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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