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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
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    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 13: String Comparator Metrics for Typographical Error
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Readers on

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Summary
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Chapter title
String Comparator Metrics for Typographical Error
Chapter number 13
Book title
Data Quality and Record Linkage Techniques
Published by
Springer, New York, NY, January 2007
DOI 10.1007/0-387-69505-2_13
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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 40%
Student > Ph. D. Student 1 20%
Other 1 20%
Student > Master 1 20%
Readers by discipline Count As %
Computer Science 3 60%
Engineering 2 40%

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