Mining Approximate Acyclic Schemes from Relations
Summary: Maimon mines approximate MVDs to derive acyclic schemes from data. It uses information-theoretic approximation to jointly mine approximate MVDs and reconstruct acyclic schemas, scalable to 1M rows and 30 columns, and robust to noise. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Batya Kenig (University of Washington)
- 2. Pranay Mundra (University of Washington)
- 3. Guna Prasaad (University of Washington)
- 4. Babak Salimi (University of Washington)
- 5. Dan Suciu (University of Washington)
BibTeX Citation
@inproceedings{kenig_sigmod20,
title = {{Mining Approximate Acyclic Schemes from Relations}},
author = {Kenig, Batya and Mundra, Pranay and Prasaad, Guna and Salimi, Babak and Suciu, Dan},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3380573},
url = {https://dl.acm.org/doi/10.1145/3318464.3380573},
year = {2020}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,441 | A Statistical Perspective on Discovering Functional Dependencies in Noisy Data | 2020 | SIGMOD | 7.4138323e-05 |
| 9,700 | Quantifying the Loss of Acyclic Join Dependencies | 2023 | PODS | 5.2351259e-05 |
| 10,652 | Smallest Synthetic Witnesses for Conjunctive Queries | 2025 | PODS | 5.093636e-05 |
| 11,564 | Statistical Schema Learning using Occam's Razor | 2022 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 358 | FAQ: Questions Asked Frequently | 2016 | PODS | 0.00020243592 |
| 495 | A Complete Axiomatization For Functional And Multivalued Dependencies In Database Relations | 1977 | SIGMOD | 0.00017513721 |
| 536 | Learning Linear Regression Models over Factorized Joins | 2016 | SIGMOD | 0.0001693369 |
| 618 | A Hybrid Approach to Functional Dependency Discovery | 2016 | SIGMOD | 0.00015711835 |
| 863 | Interventional Fairness : Causal Database Repair for Algorithmic Fairness | 2019 | SIGMOD | 0.00013531835 |
| 1,374 | Data Profiling with Metanome | 2015 | VLDB | 0.00010986078 |
| 1,500 | Efficient Discovery of Approximate Dependencies | 2018 | VLDB | 0.00010561098 |
| 2,769 | A Layered Aggregate Engine for Analytics Workloads | 2019 | SIGMOD | 8.1465406e-05 |
| 9,337 | Efficiently Enumerating Minimal Triangulations | 2017 | PODS | 5.2876688e-05 |
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