Statistical treatment of the information content of a database
Information Systems
IEEE Transactions on Software Engineering
Elements of information theory
Elements of information theory
Partial dependencies in relational databases and their realization
Discrete Applied Mathematics - Special issue on combinatorial problems in databases
Approximate inference of functional dependencies from relations
ICDT '92 Selected papers of the fourth international conference on Database theory
Asymptotic properties of keys and functional dependencies in random databases
Theoretical Computer Science - Special issue: database theory
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Principles of data mining
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Database Management Systems
Functional and embedded dependency inference: a data mining point of view
Information Systems - Special issue on Databases: creation, management and utilization
Searching for dependencies at multiple abstraction levels
ACM Transactions on Database Systems (TODS)
Relational decomposition through partial functional dependencies
Data & Knowledge Engineering
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
The Theory of Probabilistic Databases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
A Framework for Understanding Existing Databases
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Establishing the foundations of data mining
Establishing the foundations of data mining
Discovering branching and fractional dependencies in databases
Data & Knowledge Engineering
HLS: Tunable Mining of Approximate Functional Dependencies
BNCOD '08 Proceedings of the 25th British national conference on Databases: Sharing Data, Information and Knowledge
On generating near-optimal tableaux for conditional functional dependencies
Proceedings of the VLDB Endowment
Depth first algorithms and inferencing for AFD mining
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Comparable dependencies over heterogeneous data
The VLDB Journal — The International Journal on Very Large Data Bases
Letting keys and functional dependencies out of the bag
APCCM '13 Proceedings of the Ninth Asia-Pacific Conference on Conceptual Modelling - Volume 143
Editorial: Efficient discovery of similarity constraints for matching dependencies
Data & Knowledge Engineering
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We examine the issue of how to measure the degree to which a functional dependency (FD) is approximate. The primary motivation lies in the fact that approximate FDs represent potentially interesting patterns existent in a table. Their discovery is a valuable data mining problem. However, before algorithms can be developed, a measure must be defined quantifying their approximation degree.First we develop an approximation measure by axiomatizing the following intuition: the degree to which X → Y is approximate in a table T is the degree to which T determines a function from ΠX(T) to ΠY(T). We prove that a unique unnormalized measure satisfies these axioms up to a multiplicative constant. Next we compare the measure developed with two other measures from the literature. In all but one case, we show that the measures can be made to differ as much as possible within normalization. We examine these measure on several real datasets and observe that many of the theoretically possible extreme differences do not bear themselves out. We offer some conclusions as to particular situations where certain measures are more appropriate than others.