关键词: 条件函数依赖（CFDs）, 不一致数据, 最大依赖集（MDS）, 动态值域调整

Abstract: For the incomplete detection of inconsistent data by CFDs, this paper proposes a Dependency Lifting Algorithm（DLA） based on Maximum Dependency Set（MDS）, which detects inconsistent data in data set by acquiring Recessive Conditional Functional Dependencies（RCFDs） in CFDs. Presenting the dynamic domain adjustment, setting forward and backward pointers of numerical change to improve the enumeration process in original algorithm, the applicability of the algorithm to the continuous attributes is raised too. Then, this paper provides the algorithm flow and pseudo code of dynamic domain adjustment and the DLA, analyses the convergence and time complexity of them. Finally, the validity of the DLA is verified by comparing the detection accuracy and time-cost.

Key words: Conditional Functional Dependency（CFDs）, inconsistent data, Maximum Dependency Set（MDS）, dynamic domain adjustment