A Study on the Generation Method of Key Linkage Information of Pseudonymized Information for Estimating De Facto Population

The purpose of this study is to propose methods to reduce the workload associated with large-scale data processing and the generation of linkage key information for estimating the de facto population, as well as to improve the accuracy of the underlying data. The de facto population includes the resident registration population, transient population, and foreign population. It is measured monthly through the combination of pseudonymized data. The study proposes a composition of linkage keys that excludes time-series keys for efficient data combination and suggests alternative methods to address the issue of duplicate linkage keys. It is expected that this research will serve as essential foundational data for the formulation and implementation of future policies related to pseudonymized data combination.

Authors

Publication Details

Journal
The Journal of Internet Electronic Commerce Resarch
Published
2024-10-31
DOI
https://doi.org/10.37272/jiecr.2024.10.24.5.77
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
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article

A Study on the Generation Method of Key Linkage Information of Pseudonymized Information for Estimating De Facto Population

Sumi Lee, Yongtae Shin
The Journal of Internet Electronic Commerce Resarch
Data-Driven Disease Surveillance
article

A Study on the Generation Method of Key Linkage Information of Pseudonymized Information for Estimating De Facto Population

Sumi Lee, Yongtae Shin
article en

Abstract

The purpose of this study is to propose methods to reduce the workload associated with large-scale data processing and the generation of linkage key information for estimating the de facto population, as well as to improve the accuracy of the underlying data. The de facto population includes the resident registration population, transient population, and foreign population. It is measured monthly through the combination of pseudonymized data. The study proposes a composition of linkage keys that excludes time-series keys for efficient data combination and suggests alternative methods to address the issue of duplicate linkage keys. It is expected that this research will serve as essential foundational data for the formulation and implementation of future policies related to pseudonymized data combination.

The Journal of Internet Electronic Commerce ResarchVol. 24(5)
Openalex Percentile: Top 68%
Data-Driven Disease Surveillance
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A Study on the Generation Method of Key Linkage Information of Pseudonymized Information for Estimating De Facto Population — Sumi Lee, Yongtae Shin · The Journal of Internet Electronic Commerce Resarch (2024) | TGRS Research Map | TGRS