Reasoning about functional dependencies generalized for semantic data models
ACM Transactions on Database Systems (TODS)
On the Structure of Armstrong Relations for Functional Dependencies
Journal of the ACM (JACM)
Constraint-generating dependencies
Journal of Computer and System Sciences
Towards the Reverse Engineering of Denormalized Relational Databases
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Conditional functional dependencies for capturing data inconsistencies
ACM Transactions on Database Systems (TODS)
On generating near-optimal tableaux for conditional functional dependencies
Proceedings of the VLDB Endowment
Discovering data quality rules
Proceedings of the VLDB Endowment
Increasing the Expressivity of Conditional Functional Dependencies without Extra Complexity
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Discovering Conditional Functional Dependencies
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
On the computational complexity of minimal-change integrity maintenance in relational databases
Inconsistency Tolerance
Conditional functional dependencies: an FCA point of view
ICFCA'10 Proceedings of the 8th international conference on Formal Concept Analysis
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Conditional Functional Dependencies (CFDs) are Functional Dependencies (FDs) that hold on a fragment relation of the original relation. In this paper, we show the hierarchy between FDs, CFDs and Association Rules (ARs): FDs are the union of CFDs while CFDs are the union of ARs. We also show the link between Approximate Functional Dependencies (AFDs) and approximate ARs. In this paper, we show that all those dependencies are indeed structurally the same and can be unified into a single hierarchy of dependencies. A benefit of this hierarchy is that existing algorithms which discover ARs could be adapted to discover any kind of dependencies and, moreover, generate a reduced set of dependencies. We also establish the link between the problem of finding equivalent pattern tableaux of a CFD and the problem of finding keys of a relation.