Detecting duplicates in a homicide registry using a Bayesian partitioning approach
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Publication:2258589
DOI10.1214/14-AOAS779zbMath1454.62506arXiv1407.8219MaRDI QIDQ2258589
Publication date: 26 February 2015
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1407.8219
deduplicationentity resolutionrecord linkagestring similarityduplicate detectionhuman rightsdistributions on partitionsHispanic nameshomicide recordsUnited Nations Truth Commission for El Salvador
Related Items (13)
Random Partition Models for Microclustering Tasks ⋮ Entity resolution with empirically motivated priors ⋮ Bayesian propagation of record linkage uncertainty into population size estimation of human rights violations ⋮ Unique entity estimation with application to the Syrian conflict ⋮ A prior for record linkage based on allelic partitions ⋮ d-blink: Distributed End-to-End Bayesian Entity Resolution ⋮ Multifile Partitioning for Record Linkage and Duplicate Detection ⋮ Improving Probabilistic Record Linkage Using Statistical Prediction Models ⋮ A note on using the F-measure for evaluating record linkage algorithms ⋮ A unified framework for de-duplication and population size estimation (with discussion) ⋮ Detecting duplicates in a homicide registry using a Bayesian partitioning approach ⋮ Incorporating conditional dependence in latent class models for probabilistic record linkage: does it matter? ⋮ A simple two-step procedure using the Fellegi–Sunter model for frequency-based record linkage
Uses Software
Cites Work
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- A hierarchical Bayesian approach to record linkage and population size problems
- Distributions on partitions
- Detecting duplicates in a homicide registry using a Bayesian partitioning approach
- Data Quality and Record Linkage Techniques
- A Bayesian Procedure for File Linking to Analyze End-of-Life Medical Costs
- A Generalized Fellegi–Sunter Framework for Multiple Record Linkage With Application to Homicide Record Systems
- The Number of Partitions of a Set
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