Magellan: Toward Building Entity Matching Management Systems over Data Science Stacks
Summary: Magellan proposes an EM management system that extends beyond algorithms to end-to-end tooling on Python data-science stacks. It offers a step-by-step guide, full EM pipeline tooling, and an interactive scripting env for rapid experiments, evaluated with 44 users. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pradap Konda
- 2. Sanjib Das
- 3. Paul Suganthan G.C.
- 4. AnHai Doan
- 5. Adel Ardalan
- 6. Jeffrey R. Ballard
- 7. Han Li
- 8. Fatemah Panahi
- 9. Haojun Zhang
- 10. Jeff Naughton
- 11. Shishir Prasad
- 12. Ganesh Krishnan
- 13. Rohit Deep
- 14. Vijay Raghavendra
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 94 | CrowdDB: Answering Queries with Crowdsourcing | 2011 | SIGMOD | 0.00051013264 |
| 712 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00017732426 |
| 1,012 | NADEEF: A Commodity Data Cleaning System | 2013 | SIGMOD | 0.0001464733 |
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