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Trends in Applied Sciences Research
  Year: 2012 | Volume: 7 | Issue: 4 | Page No.: 285-302
DOI: 10.3923/tasr.2012.285.302
 
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CFD-Mine: An Efficient Algorithm For Discovering Functional and Conditional Functional Dependencies

Musbah M. Aqel, Nidal F. Shilbayeh and Mohammed S. Hakawati

Abstract:
Dirty data is a serious problem that affects many enterprises across all aspects of their business ranging from operational efficiency to revenue protection. In this study, we present a new algorithm called CFD-Mine that efficiently discovers all possible rules and determines the minimum set of these rules using functional Dependencies (FDs) and Conditional Functional Dependencies (CFDs) for detecting inconsistencies in data. The algorithm is based on the level-wise search algorithm that extends TANE, a well-known algorithm for discovering FDs. CFD-Mine searches for the minimum CFDs among the data values and prunes redundant candidates. The conducted experiments show that CFD-Mine is scalable and applicable to work efficiently when the data sets are large.
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How to cite this article:

Musbah M. Aqel, Nidal F. Shilbayeh and Mohammed S. Hakawati, 2012. CFD-Mine: An Efficient Algorithm For Discovering Functional and Conditional Functional Dependencies. Trends in Applied Sciences Research, 7: 285-302.

DOI: 10.3923/tasr.2012.285.302

URL: https://scialert.net/abstract/?doi=tasr.2012.285.302

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