RadlER: Deduplicated Sampling On-Demand
Summary: RadlER enables deduplicated sampling on-demand by incrementally cleaning only the entities required to meet a target distribution over subpopulations, avoiding costly full-dataset deduplication. Interactive demo shows a workflow that saves substantial time and resources for downstream analyses. (summarized by gpt-5-mini on Feb 09 2026)
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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 |
|---|---|---|---|---|
| 5,428 | Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching | 2023 | VLDB | 6.2932384e-05 |
| 7,692 | Entity Resolution On-Demand | 2022 | VLDB | 5.6231744e-05 |
| 9,462 | BrewER: Entity Resolution On-Demand | 2023 | VLDB | 5.3271933e-05 |
| 10,625 | Deduplicated Sampling On-Demand | 2025 | VLDB | 5.1725247e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,946 | Sampling Dirty Data for Matching Attributes | 2010 | SIGMOD | 6.4974038e-05 |
| 3,951 | Crowd-Based Deduplication: An Adaptive Approach | 2015 | SIGMOD | 7.0687525e-05 |
| 8,326 | DADER: Hands-Off Entity Resolution with Domain Adaptation | 2022 | VLDB | 5.5073387e-05 |
| 2,052 | Dedoop: Efficient Deduplication with Hadoop | 2012 | VLDB | 9.3268877e-05 |
| 8,937 | R2D2: Reducing Redundancy and Duplication in Data Lakes | 2023 | SIGMOD | 5.4076395e-05 |
| 7,692 | Entity Resolution On-Demand | 2022 | VLDB | 5.6231744e-05 |
| 5,352 | MDedup: Duplicate Detection with Matching Dependencies | 2020 | VLDB | 6.3223357e-05 |
| 3,614 | NADEEF/ER: Generic and Interactive Entity Resolution | 2014 | SIGMOD | 7.3242655e-05 |
| 9,462 | BrewER: Entity Resolution On-Demand | 2023 | VLDB | 5.3271933e-05 |
| 10,625 | Deduplicated Sampling On-Demand | 2025 | VLDB | 5.1725247e-05 |