Magellan: Toward Building Entity Matching Management Systems
Summary: Magellan reframes entity matching as an end-to-end EM management system, not just algorithms. It offers step-by-step guides, a Python-based toolchain across the EM pipeline, and an interactive scripting environment, validated by 44 users. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pradap Konda (University of Wisconsin)
- 2. Sanjib Das (University of Wisconsin)
- 3. Paul Suganthan G.C. (University of Wisconsin)
- 4. AnHai Doan (University of Wisconsin)
- 5. Adel Ardalan (University of Wisconsin)
- 6. Jeffrey R. Ballard (University of Wisconsin)
- 7. Han Li (University of Wisconsin)
- 8. Fatemah Panahi (University of Wisconsin)
- 9. Haojun Zhang (University of Wisconsin)
- 10. Jeff Naughton (University of Wisconsin)
- 11. Shishir Prasad (Instacart)
- 12. Ganesh Krishnan (Walmart Labs)
- 13. Rohit Deep (Walmart Labs)
- 14. Vijay Raghavendra (Walmart Labs)
BibTeX Citation
@article{konda_vldb16,
title = {{Magellan: Toward Building Entity Matching Management Systems}},
author = {Konda, Pradap and Das, Sanjib and G.C., Paul Suganthan and Doan, AnHai and Ardalan, Adel and Ballard, Jeffrey R. and Li, Han and Panahi, Fatemah and Zhang, Haojun and Naughton, Jeff and Prasad, Shishir and Krishnan, Ganesh and Deep, Rohit and Raghavendra, Vijay},
journal = {PVLDB},
series = {{VLDB} '16},
volume = {9},
number = {12},
pages = {1197--1208},
doi = {10.14778/2994509.2994518},
url = {https://doi.org/10.14778/2994509.2994518},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 50 of 51 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 90 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00034951786 |
| 356 | Efficient Parallel Set-Similarity Joins Using MapReduce | 2010 | SIGMOD | 0.00020303289 |
| 439 | Corleone: Hands-Off Crowdsourcing for Entity Matching | 2014 | SIGMOD | 0.00018464913 |
| 528 | On Active Learning of Record Matching Packages | 2010 | SIGMOD | 0.00017100838 |
| 725 | NADEEF: A Commodity Data Cleaning System | 2013 | SIGMOD | 0.00014617251 |
| 1,293 | Entity Resolution with Iterative Blocking | 2009 | SIGMOD | 0.00011292804 |
| 2,055 | Dedoop: Efficient Deduplication with Hadoop | 2012 | VLDB | 9.2512023e-05 |
| 2,893 | Distributed Data Deduplication | 2016 | VLDB | 7.983961e-05 |
| 3,883 | Magellan: Toward Building Entity Matching Management Systems over Data Science Stacks | 2016 | VLDB | 7.0487615e-05 |
| 5,246 | Entity Extraction, Linking, Classification, and Tagging for Social Media: A Wikipedia-Based Approach | 2013 | VLDB | 6.3012556e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,643 | Falcon: Scaling Up Hands-Off Crowdsourced Entity Matching to Build Cloud Services | 2017 | SIGMOD |
| 2 | 11,726 | Valentine in Action: Matching Tabular Data at Scale | 2021 | VLDB |
| 3 | 5,293 | Magneto: Combining Small and Large Language Models for Schema Matching | 2025 | VLDB |
| 4 | 9,015 | Analyzing and Revising Data Integration Schemas to Improve Their Matchability | 2008 | VLDB |
| 5 | 6,041 | Demonstration of Panda: A Weakly Supervised Entity Matching System | 2021 | VLDB |
| 6 | 9,121 | Entity Matching in the Wild: A Consistent and Versatile Framework to Unify Data in Industrial Applications | 2020 | SIGMOD |
| 7 | 11,945 | CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching | 2018 | VLDB |
| 8 | 176 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD |
| 9 | 7,373 | Entity Matching Meets Data Science: A Progress Report from the Magellan Project | 2019 | SIGMOD |
| 10 | 3,883 | Magellan: Toward Building Entity Matching Management Systems over Data Science Stacks | 2016 | VLDB |