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Discovery Algorithms for Embedded Functional Dependencies

Summary: eFD discovery is NP-complete and W[2]-hard in the output, with a larger minimum solution space than classical FDs. Row-, column-, and hybrid data structures with efficient search enable scalable eFD discovery; ranking by redundant values highlights meaningful eFDs and showcases completeness benefits for approximate and genuine FDs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6002
Venue
SIGMOD
Year
2020
Pagerank
4.7469673e-05
Overall Rank
7,361 | 48.85%
DOI
10.1145/3318464.3389786

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank Citing Paper Year Venue Pagerank
5,911 Normalizing Property Graphs 2023 VLDB 5.2718035e-05
8,836 Fast Approximate Denial Constraint Discovery 2023 VLDB 4.4350633e-05
9,647 Discovering Functional Dependencies through Hitting Set Enumeration 2024 SIGMOD 4.3067693e-05
9,748 Efficient Differential Dependency Discovery 2024 VLDB 4.2856385e-05
10,595 Efficient Discovery of Relaxed Functional Dependencies 2025 VLDB 4.1905499e-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.

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