期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：2
DOI：10.15680/ijircce.2015.0302051
出版社：S&S Publications
摘要：This paper details about various methods to discover functional dependencies from data.Effectivepruning for the discovery of conditional functional dependencies is discussed in detail. Di conditional FunctionalDependencies and Fast FDs a heuristic-driven, Depth-first algorithm for mining FD from relation instances areelaborated. Privacy preserving publishing micro data with Full Functional Dependencies and Conditional functionaldependencies for capturing data inconsistencies are examined. The approximation measures for functionaldependencies and the complexity of inferring functional dependencies are also observed. Compression - BasedEvaluation of partial determinations is portrayed. This survey would promote a lot of research in the area of miningfunctional dependencies from data.
关键词：Effective Pruning; Conditional Functional Dependency (DFD); Mining; Data Anonymization;Similarity Constraints
