Functional Dependency Inference Problem

The functional dependency inference problem is to find a cover for the set of functional dependencies that hold in a given relation. A functional dependency (abbr. FD), ff, is a statement f:XYf: X \rightarrow Y where XX and YY are sets of attributes. If R(X,Y,)R(X, Y, \ldots) is a relation on a set of attributes that contains XX and YY, then RR obeys the FD ff if every two tuples of RR which have the same projection on XX also have the same projection on YY. Given f:XYf: X \rightarrow Y, we say that ff is a functional dependency from XX to YY, that YY is functionally dependent on XX or that XX functionally determines YY. From the definition it follows that for each pair of sets XX and YY there is at most one functional dependency from XX to YY. Therefore, we usually omit the name of the FD and write XYX \rightarrow Y.

Parameters

  • nn: number of attributes
  • pp: number of tuples/rows/data points

Filters

Computational Model

Randomization

Approximation

Algorithms Table

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Schlimmer1993O(n2np)O(n 2^n p)O(2n)O(2^n)
Brute force algorithm1967O(n22nplogp)O(n^2 2^n p \log p)O(n2n)O(n2^n)

Reductions Table

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Other relevant algorithms

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