Efficient Discovery of Approximate Dependencies
Summary: Efficient discovery of approximate FDs and approximate UCCs. Pyro combines separate-and-conquer search with sampling-guided verification to quickly propose and validate candidates; scales to large datasets with minimal memory, outperforming prior methods by up to 33×. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Sebastian Kruse (Hasso Plattner Institute)
- 2. Felix Naumann (Hasso Plattner Institute)
BibTeX Citation
@article{kruse_vldb18,
title = {{Efficient Discovery of Approximate Dependencies}},
author = {Kruse, Sebastian and Naumann, Felix},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {7},
pages = {759--772},
doi = {10.14778/3192965.3192968},
url = {https://doi.org/10.14778/3192965.3192968},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
Showing 27 of 27 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 647 | Discovering Data Quality Rules | 2008 | VLDB |
| 2 | 9,923 | Efficient Differential Dependency Discovery | 2024 | VLDB |
| 3 | 9,780 | Discovering Functional Dependencies through Hitting Set Enumeration | 2024 | SIGMOD |
| 4 | 8,684 | Workload-driven, Lazy Discovery of Data Dependencies for Query Optimization | 2022 | CIDR |
| 5 | 10,848 | Efficient Discovery of Relaxed Functional Dependencies | 2025 | VLDB |
| 6 | 10,812 | Discovering Approximate Inclusion Dependencies | 2025 | VLDB |
| 7 | 7,187 | Discovery Algorithms for Embedded Functional Dependencies | 2020 | SIGMOD |
| 8 | 11,743 | Making DBMSes Dependency-Aware | 2020 | CIDR |
| 9 | 729 | Functional Dependency Discovery: An Experimental Evaluation of Seven Algorithms | 2015 | VLDB |
| 10 | 618 | A Hybrid Approach to Functional Dependency Discovery | 2016 | SIGMOD |