mlsanityData to 7 Oct 2026

Estimating the Performance of Entity Resolution Algorithms: Lessons Learned Through PatentsView.org

arXiv 2210.01230 ↗First posted 3 Oct 2022cs.DL cs.DB cs.LGcited by 3

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Abstract (arXiv)

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

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 9 of its 59 references that are in the map. First posted on arXiv 3 Oct 2022.

Builds on

9 of 59 references.

References · 9

  1. 2020(Almost) All of Entity Resolutioncited by 23
  2. 2021S2AND: A Benchmark and Evaluation System for Author Name Disambiguationcited by 13
  3. 2022Bridging the Gap between Reality and Ideality of Entity Matching: A Revisiting and Benchmark Re-Constructioncited by 10
  4. 2019Optimal Transport-based Alignment of Learned Character Representations for String Similaritycited by 7
  5. 2019Scalable Hierarchical Clustering with Tree Graftingcited by 7
  6. 2017In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Samplingcited by 4
  7. 2019Scaling Bayesian Probabilistic Record Linkage with Post-Hoc Blocking: An Application to the California Great Registerscited by 4
  8. 2015A Practioner's Guide to Evaluating Entity Resolution Resultscited by 2
  9. 2016Random Forest DBSCAN for USPTO Inventor Name Disambiguationcited by 1

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Cited by year

Citing papers per year: 2023: 1; 2024: 2.

3 papers.

  1. 2024Improving the Validity and Practical Usefulness of AI/ML Evaluations Using an Estimands Frameworkcited by 4
  2. 2023PatentsView-Evaluation: Evaluation Datasets and Tools to Advance Research on Inventor Name Disambiguationcited by 1
  3. 2024How to Evaluate Entity Resolution Systems: An Entity-Centric Framework with Application to Inventor Name Disambiguationcited by 1