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Data Quality and Record Linkage Techniques

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Cover of 'Data Quality and Record Linkage Techniques'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction
  3. Altmetric Badge
    Chapter 2 What is Data Quality and Why Should We Care?
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    Chapter 3 Examples of Entities Using Data\break to their Advantage/Disadvantage
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    Chapter 4 Properties of Data Quality and Metrics for Measuring It
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    Chapter 5 Basic Data Quality Tools
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    Chapter 6 Mathematical Preliminaries for Specialized Data Quality Techniques
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    Chapter 7 Automatic Editing and Imputation of Sample Survey Data
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    Chapter 8 Record Linkage – Methodology
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    Chapter 9 Estimating the Parameters of the Fellegi–Sunter Record Linkage Model
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    Chapter 10 Standardization and Parsing
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    Chapter 11 Phonetic Coding Systems for Names
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    Chapter 12 Blocking
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    Chapter 13 String Comparator Metrics for Typographical Error
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    Chapter 14 Duplicate FHA Single-Family Mortgage Records
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    Chapter 15 Record Linkage Case Studies in the Medical, Biomedical, and Highway Safety Areas
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    Chapter 16 Constructing List Frames and Administrative Lists
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    Chapter 17 Social Security and Related Topics
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    Chapter 18 Confidentiality: Maximizing Access to Micro-data while Protecting Privacy
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    Chapter 19 Review of Record Linkage Software
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    Chapter 20 Summary Chapter
Attention for Chapter 2: What is Data Quality and Why Should We Care?
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Readers on

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41 Mendeley
Summary
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Chapter title
What is Data Quality and Why Should We Care?
Chapter number 2
Book title
Data Quality and Record Linkage Techniques
Published by
Springer, New York, NY, January 2007
DOI 10.1007/0-387-69505-2_2
Book ISBNs
978-0-387-69502-0, 978-0-387-69505-1
Authors

Thomas N. Herzog, Fritz J. Scheuren, William E. Winkler

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 32%
Student > Ph. D. Student 11 27%
Student > Bachelor 4 10%
Researcher 4 10%
Other 1 2%
Other 1 2%
Unknown 7 17%
Readers by discipline Count As %
Computer Science 14 34%
Business, Management and Accounting 6 15%
Social Sciences 4 10%
Arts and Humanities 2 5%
Psychology 2 5%
Other 6 15%
Unknown 7 17%

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