ActivePDB: Active Probabilistic Databases
Summary: ActivePDB proposes an end-to-end framework for uncertain relational data with an oracle for verification. It uses provenance to map outputs to inputs and active learning to minimize verifications, updating probabilities; demonstrated on NELL. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Osnat Drien
- 2. Matanya Freiman
- 3. Yael Amsterdamer
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Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 31 | Provenance Semirings | 2007 | PODS | 0.00078516827 |
| 192 | HoloClean: Holistic Data Repairs with Probabilistic Inference | 2017 | VLDB | 0.00035692958 |
| 1,544 | KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing | 2015 | SIGMOD | 0.00011438274 |
| 2,805 | Query-Oriented Data Cleaning with Oracles | 2015 | SIGMOD | 8.103731e-05 |
| 5,254 | CDB: A Crowd-Powered Database System | 2018 | VLDB | 5.5991922e-05 |
| 6,707 | Consistent Query Answers in Inconsistent Probabilistic Databases | 2010 | SIGMOD | 4.9500448e-05 |
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