Mining Meaningful Keys and Foreign Keys with High Precision and Recall

Summary: E/R Profiler that mines a strict hierarchy of key variants (candidate keys → SQL uniqueness) with algorithms for approximate-key discovery under arity, completeness, dirtiness and orthogonality thresholds. Novel orthogonality metric separates accidental from meaningful keys, enabling high-precision/-recall key and FK discovery to reveal entity and referential constraints. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14345
Venue: VLDB
Year: 2025
Pagerank: 5.093636e-05
Overall Rank: 11,044 | 24.23%
DOI: 10.14778/3750601.3750672

Incoming Non-self Citations Over Time

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Authors

1. Henning Koehler (DataViadotto Limited)
2. Sebastian Link (DataViadotto Limited)

BibTeX Citation

@article{koehler_vldb25,
        title = {{Mining Meaningful Keys and Foreign Keys with High Precision and Recall}},
        author = {Koehler, Henning and Link, Sebastian},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {12},
        pages = {5363--5366},
        doi = {10.14778/3750601.3750672},
        url = {https://doi.org/10.14778/3750601.3750672},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,374	Data Profiling with Metanome	2015	VLDB	0.00010986078
6,827	Sampling Dirty Data for Matching Attributes	2010	SIGMOD	5.7616041e-05

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