A Bayesian Approach for De-duplication in the Presence of Relational Data

Juan Sosa; Abel Rodriguez

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arXiv · 1909.06519

A Bayesian Approach for De-duplication in the Presence of Relational Data

Juan Sosa·Abel Rodriguez

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Abstract

In this paper, we study the impact of combining profile and network data in a de-duplication setting. We also assess the influence of a range of prior distributions on the linkage structure. Furthermore, we explore stochastic gradient Hamiltonian Monte Carlo methods as a faster alternative to obtain samples from the posterior distribution for network parameters. Our methodology is evaluated using the RLdata500 data, which is a popular dataset in the record linkage literature.

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Juan Sosa, Abel Rodriguez. 2021-11-16. A Bayesian Approach for De-duplication in the Presence of Relational Data. https://arxiv.org/abs/1909.06519

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