d-blink: Distributed End-to-End Bayesian Entity Resolution

DOI10.1080/10618600.2020.1825451OpenAlexW3088072504MaRDI QIDQ5066405

Rebecca C. Steorts, Daniel N. Elazar, Neil G. Marchant, Andee Kaplan, Benjamin I. P. Rubinstein

Publication date: 29 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10618600.2020.1825451

zbMATH Keywords

Markov chain Monte Carloauxiliary variabledistributed computingrecord linkagepartially collapsed Gibbs sampling

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Multifile Partitioning for Record Linkage and Duplicate Detection

Uses Software

• RecordLinkage

Cites Work

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• Entity resolution with empirically motivated priors
• A hierarchical Bayesian approach to record linkage and population size problems
• A unified framework for de-duplication and population size estimation (with discussion)
• Detecting duplicates in a homicide registry using a Bayesian partitioning approach
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Data Quality and Record Linkage Techniques
• Partially Collapsed Gibbs Samplers
• Multidimensional binary search trees used for associative searching
• An Algorithm for Finding Best Matches in Logarithmic Expected Time
• A Bayesian Procedure for File Linking to Analyze End-of-Life Medical Costs
• Multivariate output analysis for Markov chain Monte Carlo
• Informed Proposals for Local MCMC in Discrete Spaces
• A Generalized Fellegi–Sunter Framework for Multiple Record Linkage With Application to Homicide Record Systems
• Regression Analysis With Linked Data

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