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Formalization and Discovery of Approximate Conditional Functional Dependencies

  • Hiroki Nakayama
  • Ayako Hoshino
  • Chihiro Ito
  • Kyota Kanno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8055)

Abstract

We propose efficient and precise discoveries of approximate Conditional Functional Dependencies (CFDs), by providing a precise formalization of approximate CFDs and presenting three discovery algorithms approxCFDMiner, approxCTANE and approxFastCFD as extensions of existing algorithms with renewed techniques. First, approxCFDMiner introduces a global FP-tree traversal for finding Right-hand Side items. Second, approxCTANE uses a modified pruning strategy. Third, approxFastCFD adopts a minimal coverset that is used to exclude non-minimal approximate CFDs. For these algorithms, we theoretically proved the correctness and experimentally evaluated the performances.

Keywords

Conditional Functional Dependency Approximate CFD Discovery Algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hiroki Nakayama
    • 1
  • Ayako Hoshino
    • 2
  • Chihiro Ito
    • 2
  • Kyota Kanno
    • 2
  1. 1.NEC Informatec Systems, Ltd.Kawasaki-shiJapan
  2. 2.NEC Knowledge Discovery Research Labs.Kawasaki-shiJapan

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