The Soundex Blocking: A Novel Blocking Approach for Record Linkage

The problem of record linkage is to cluster the records from several data sources such that each cluster has all the records belonging to one and only one entity. Record linkage has applications in a wide variety of domains including public health, law enforcement, fraud detection, biology, and transportation. Given the typically vast sizes of datasets, existing algorithms suffer from very long runtimes. Hence, it is essential to develop novel algorithms tailored to address this issue. Blocking is a popular technique employed to speed up record linkage algorithms. In this paper, we employ a blocking technique that is based on Soundex encoding. Soundex index is a method of coding names based on their pronunciation rather than their spelling. Soundex has been traditionally used only as a distance metric. In this paper, we show how to use Soundex as a blocking technique. To the best of our knowledge, no one else has done it in the past. In fact, we introduce two novel blocking approaches that utilize Soundex encoding: One stage Soundex blocking and Two stage Soundex blocking.Our approaches exhibit superior linkage performance compared to the state-of-the-art record linkage algorithms, as evidenced by higher F-1 scores and reduced linkage times. The proposed blocking approaches prove to be highly effective.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825041
Citations
2
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.98

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article

The Soundex Blocking: A Novel Blocking Approach for Record Linkage

K. Park, Anup Mathur, Sanguthevar Rajasekaran, Sartaj Sahni et al.
2 citations
Data Quality and Management
0.98
article

The Soundex Blocking: A Novel Blocking Approach for Record Linkage

K. Park, Anup Mathur, Sanguthevar Rajasekaran, Sartaj Sahni, Ahmed Soliman, Kenneth B. Haase, Nidhibahen Shah, Daniel H. Weinberg, Joyanta Basak, Jonathan White
article en
2 citations

Abstract

The problem of record linkage is to cluster the records from several data sources such that each cluster has all the records belonging to one and only one entity. Record linkage has applications in a wide variety of domains including public health, law enforcement, fraud detection, biology, and transportation. Given the typically vast sizes of datasets, existing algorithms suffer from very long runtimes. Hence, it is essential to develop novel algorithms tailored to address this issue. Blocking is a popular technique employed to speed up record linkage algorithms. In this paper, we employ a blocking technique that is based on Soundex encoding. Soundex index is a method of coding names based on their pronunciation rather than their spelling. Soundex has been traditionally used only as a distance metric. In this paper, we show how to use Soundex as a blocking technique. To the best of our knowledge, no one else has done it in the past. In fact, we introduce two novel blocking approaches that utilize Soundex encoding: One stage Soundex blocking and Two stage Soundex blocking.Our approaches exhibit superior linkage performance compared to the state-of-the-art record linkage algorithms, as evidenced by higher F-1 scores and reduced linkage times. The proposed blocking approaches prove to be highly effective.

United States Census Bureau (US), University of Connecticut (US), University of Florida (US)
Yale University, U.S. Census Bureau
Openalex Percentile: Top 19%
Data Quality and Management
0.98
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