Overview
- First book on a topic of growing importance for applications
- Brings together research from various areas like databases, statistics, information retrieval, data mining, and machine learning
- Details the data matching process step by step
- Includes an overview of freely available data matching systems and a detailed discussion of practical aspects and limitations
- Includes supplementary material: sn.pub/extras
- Includes supplementary material: sn.pub/extras
Part of the book series: Data-Centric Systems and Applications (DCSA)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
-
Front Matter
-
Overview
-
Front Matter
-
-
Steps of the Data Matching Process
-
Front Matter
-
-
Steps of the DataMatching Process
-
Further Topics
-
Front Matter
-
-
Back Matter
Keywords
About this book
Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases.
Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today.
By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially,they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.Reviews
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Data Matching
Book Subtitle: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection
Authors: Peter Christen
Series Title: Data-Centric Systems and Applications
DOI: https://doi.org/10.1007/978-3-642-31164-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2012
Hardcover ISBN: 978-3-642-31163-5Published: 05 July 2012
Softcover ISBN: 978-3-642-43001-5Published: 09 August 2014
eBook ISBN: 978-3-642-31164-2Published: 04 July 2012
Series ISSN: 2197-9723
Series E-ISSN: 2197-974X
Edition Number: 1
Number of Pages: XX, 272
Topics: Database Management, Data Mining and Knowledge Discovery, Information Storage and Retrieval, Artificial Intelligence, Pattern Recognition