FairEM360: A Suite for Responsible Entity Matching
Summary: FairEM360: end-to-end suite to audit, explain, and remediate fairness in entity matching across multiple fairness metrics and paradigms. Provides human-in-the-loop explanations and ensemble matchers to diagnose and correct data- or matcher-induced biases pre-deployment. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Nima Shahbazi
- 2. Mahdi Erfanian
- 3. Abolfazl Asudeh
- 4. Fatemeh Nargesian
- 5. Divesh Srivastava
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 221 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.00033121824 |
| 300 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00028441466 |
| 712 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00017732426 |
| 4,018 | Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching | 2023 | VLDB | 6.5244015e-05 |
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