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Discovering Functional Dependencies through Hitting Set Enumeration

Summary: FDhits finds all valid, minimal FDs via hitting-set enumeration, with hybrid validation and one-pass candidate checks, plus parallelization. It yields a median 8.1× speedup over prior work with lower memory, enabling FD profiling on larger datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
he644929a0dd626f9
Venue
SIGMOD
Year
2024
Pagerank
5.1038322e-05
Overall Rank
9,958 | 33.05%
DOI
10.1145/3639298

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{bleifu_sigmod24,
        title = {{Discovering Functional Dependencies through Hitting Set Enumeration}},
        author = {Bleifuß, Tobias and Papenbrock, Thorsten and Bläsius, Thomas and Schirneck, Martin and Naumann, Felix},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639298},
        url = {https://dl.acm.org/doi/10.1145/3639298},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
10,953 HaDA: Empower Database Experts with Data Dependencies 2026 VLDB 4.9793485e-05
11,254 Efficient Discovery of Relaxed Functional Dependencies 2025 VLDB 4.9793485e-05
11,316 Meaningful Data Erasure in the Presence of Dependencies 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

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

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