Whether the goal is to estimate the number of people that live in a congressional district, to
estimate the number of individuals that have died in an armed conflict, or to disambiguate …

Health policy evidence-building requires data sources such as health care claims, electronic
health records, probability and nonprobability survey data, epidemiological surveillance …

Merging datafiles containing information on overlapping sets of entities is a challenging task
in the absence of unique identifiers, and is further complicated when some entities are …

A single dataset is rarely sufficient to address a question of substantive interest. Instead,
most applied data analysis combines data from multiple sources. Very rarely do two datasets …

A Unified Framework for De-Duplication and Population Size Estimation (with Discussion)
Page 1 Bayesian Analysis (2020) 15, Number 2, pp. 633–682 A Unified Framework for De-Duplication …

Entity resolution is the process of merging and removing duplicate records from multiple
data sources, often in the absence of unique identifiers. Bayesian models for entity …

The availability of both structured and unstructured databases, such as electronic health
data, social media data, patent data, and surveys that are often updated in real time, among …

Entity resolution (ER; also known as record linkage or de-duplication) is the process of
merging noisy databases, often in the absence of unique identifiers. A major advancement …

This article introduces a novel evaluation methodology for entity resolution algorithms. It is
motivated by PatentsView. org, a public-use patent data exploration platform that …

Record linkage brings together information from records in two or more data sources that are
believed to belong to the same statistical unit based on a common set of matching variables …