Multivalued Dependency Inference Problem

The multivalued dependency inference problem is to find a cover for the set of multivalued dependencies that hold in a given relation. A multivalued dependency (abbr. MVD), gg, on a set of attributes UU is a statement g:XYg: X \rightarrow \rightarrow Y, where XX and YY are subsets of UU. Let ZZ be the complement of the union of XX and YY in UU. A relation R(U)R(U) obeys the MVD g:XYg: X \rightarrow \rightarrow Y if for every XZXZ-value, xzxz, that appears in RR, we have YR(xz)=YR(x)Y_R(xz) = Y_R (x). In words, the MVD gg is valid in RR if the set of YY-values that appears in RR with a given xx appears with every combination of xx and zz in RR. Thus, this set is a function of xx alone and does not depend on the ZZ-values that appear with xx. Given g:XYg: X \rightarrow \rightarrow Y, we say that gg is a multivalued dependency from XX to YY (in the set UU). As we do for functional dependencies (FD's), here also we usually omit the name gg of the MVD and just write XYX \rightarrow \rightarrow Y.

Parameters

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

Filters

Computational Model

Randomization

Approximation

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Räihä; Manilla1992O(n22nplogp)O(n^2 2^n p \log p)O(n2n)O(n2^n)

Reductions Table

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