FD/spl I.bar/Mine: discovering functional dependencies in a database using equivalences

The discovery of FDs from databases has recently become a significant research problem. In this paper, we propose a new algorithm, called FD-Mine. FD-Mine takes advantage of the rich theory of FDs to reduce both the size of the dataset and the number of FDs to be checked by using discovered equivale...

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Main Authors: Hong Yao, Hamilton, H.J., Butz, C.J.
Format: Conference Proceeding
Language:English
Subjects:
Chemical compounds
Computer science
Independent component analysis
Lattices
Partitioning algorithms
Relational databases
Sorting
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Hamilton, H.J.
Butz, C.J.
description The discovery of FDs from databases has recently become a significant research problem. In this paper, we propose a new algorithm, called FD-Mine. FD-Mine takes advantage of the rich theory of FDs to reduce both the size of the dataset and the number of FDs to be checked by using discovered equivalences. We show that the pruning does not lead to loss of information. Experiments on 15 UCI datasets show that FD-Mine can prune more candidates than previous methods.
doi_str_mv 10.1109/ICDM.2002.1184040
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subjects Chemical compounds
Computer science
Independent component analysis
Lattices
Partitioning algorithms
Relational databases
Sorting
title FD/spl I.bar/Mine: discovering functional dependencies in a database using equivalences
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