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Entity Resolution and Information Quality
1st Edition - December 8, 2010
Author: John R. Talburt
Paperback ISBN:
9 7 8 - 0 - 1 2 - 3 8 1 9 7 2 - 7
eBook ISBN:
9 7 8 - 0 - 1 2 - 3 8 1 9 7 3 - 4
Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a… Read more
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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.
- 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.
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.
ForewordPrefaceAcknowledgementsChapter 1 Principles of Entity Resolution Entity Resolution Entity Resolution Activities Summary Review QuestionsChapter 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 QuestionsChapter 3 Entity Resolution Models Overview The Fellegi-Sunter Model SERF Model Algebraic Model ENRES Meta-Model Summary Review QuestionsChapter 4 Entity-Based Data Integration Introduction Formal Framework for Describing EBDI Optimizing Selection Operator Accuracy More Complex Selection Rules Summary Review QuestionsChapter 5 Entity Resolution Systems Introduction DataFlux dfPowerStudio Infoglide Identity Resolution Engine Acxiom AbiliTec Summary Review QuestionsChapter 6 The OYSTER Project Background OYSTER Logic Transitive Equivalence Example Asserted Equivalence Example Febrl: Open-Source Project Summary Review QuestionsChapter 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 QuestionsBibliographyGlossaryAppendixIndex
- No. of pages: 256
- Language: English
- Published: December 8, 2010
- Imprint: Morgan Kaufmann
- Paperback ISBN: 9780123819727
- eBook ISBN: 9780123819734
JT
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.
Affiliations and expertise
Professor of Information Science, University of Arkansas at Little Rock, AR, USA