Entity Matching Meets Data Science: A Progress Report from the Magellan Project
Summary: Magellan treats entity matching as a data-science ecosystem with interoperable tools (PyMatcher, CloudMatcher) for power and lay users. Over 3.5 years, it reports production deployments across 21 EM tasks in 12 companies and a cloud-native, Docker/Kubernetes ecosystem. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yash Govind (University of Wisconsin)
- 2. Pradap Konda (Meta)
- 3. Paul Suganthan G. C. (Google)
- 4. Philip Martinkus (University of Wisconsin)
- 5. Palaniappan Nagarajan (Amazon)
- 6. Han Li (University of Wisconsin)
- 7. Aravind Soundararajan (University of Wisconsin)
- 8. Sidharth Mudgal (Amazon)
- 9. Jeffrey R. Ballard (University of Wisconsin)
- 10. Haojun Zhang (University of Wisconsin)
- 11. Adel Ardalan (Columbia University)
- 12. Sanjib Das (Google)
- 13. Derek Paulsen (University of Wisconsin)
- 14. Amanpreet Saini (University of Wisconsin)
- 15. Erik Paulson (Johnson Controls)
- 16. Youngchoon Park (Johnson Controls)
- 17. Marshall Carter (American Family Insurance)
- 18. Mingju Sun (American Family Insurance)
- 19. Glenn M. Fung (American Family Insurance)
- 20. AnHai Doan (University of Wisconsin)
BibTeX Citation
@inproceedings{govind_sigmod19,
title = {{Entity Matching Meets Data Science: A Progress Report from the Magellan Project}},
author = {Govind, Yash and Konda, Pradap and C., Paul Suganthan G. and Martinkus, Philip and Nagarajan, Palaniappan and Li, Han and Soundararajan, Aravind and Mudgal, Sidharth and Ballard, Jeffrey R. and Zhang, Haojun and Ardalan, Adel and Das, Sanjib and Paulsen, Derek and Saini, Amanpreet and Paulson, Erik and Park, Youngchoon and Carter, Marshall and Sun, Mingju and Fung, Glenn M. and Doan, AnHai},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3314042},
url = {https://dl.acm.org/doi/10.1145/3299869.3314042},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,905 | Medical Entity Disambiguation Using Graph Neural Networks | 2021 | SIGMOD | 6.4497268e-05 |
| 6,167 | Sparkly: A Simple yet Surprisingly Strong TF/IDF Blocker for Entity Matching | 2023 | VLDB | 5.9524736e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 176 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00027191081 |
| 529 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00017096361 |
| 1,643 | Falcon: Scaling Up Hands-Off Crowdsourced Entity Matching to Build Cloud Services | 2017 | SIGMOD | 0.00010134956 |
| 2,623 | The return of JedAI: End-to-End Entity Resolution for Structured and Semi-Structured Data | 2018 | VLDB | 8.3327284e-05 |
| 3,112 | The Garlic Project | 1996 | SIGMOD | 7.7417186e-05 |
| 4,023 | Smurf: Self-Service String Matching Using Random Forests | 2019 | VLDB | 6.949387e-05 |
| 11,945 | CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching | 2018 | VLDB | 5.093636e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,248 | Entity Matching: How Similar Is Similar | 2011 | VLDB |
| 2 | 9,992 | Progressive Entity Matching: A Design Space Exploration | 2025 | SIGMOD |
| 3 | 248 | Evaluation of entity resolution approaches on real-world match problems | 2010 | VLDB |
| 4 | 4,056 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | 2020 | VLDB |
| 5 | 9,015 | Analyzing and Revising Data Integration Schemas to Improve Their Matchability | 2008 | VLDB |
| 6 | 9,121 | Entity Matching in the Wild: A Consistent and Versatile Framework to Unify Data in Industrial Applications | 2020 | SIGMOD |
| 7 | 176 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD |
| 8 | 11,945 | CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching | 2018 | VLDB |
| 9 | 529 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB |
| 10 | 3,883 | Magellan: Toward Building Entity Matching Management Systems over Data Science Stacks | 2016 | VLDB |