Given a set of records, entity resolution algorithms find allthe records referring to each entity. In this paper, we studythe problem of top-k entity resolution: finding all the recordsreferring to the k largest (in terms of records) entities. Top-kentity resolution is driven by many modern applications thatoperate over just the few most popular entities in a dataset.We ...

This chapter introduces abstract algebra as a means of understanding and creating data quality metrics for entity resolution, the process in which records determined to represent the same real-world entity are successively located and merged. Entity resolution is a particular form of data mining that is foundational to a number of applications in both industry and government. Examples include c...

This paper introduces a novel evaluation methodology for entity resolution algorithms. It is motivated by PatentsView.org, U.S. Patents and Trademarks Office patent data exploration tool that disambiguates inventors using an algorithm. We provide collection tailored performance estimators account sampling biases. Our approach simple, practical principled -- key characteristics allow us to paint...