一种基于CFDs规则的修复序列快速判定方法

Rapid Decision Method for Repairing Sequence Based on CFDs

数据一致性是大数据质量管理研究的一个重要内容。条件函数依赖(CFDs)是维护数据一致性的有效技术手段。然而,在修复过程中选择不同的CFDs修复顺序,会影响修复的准确性和效率。因此,如何选取一个正确且合理的修复顺序对数据修复至关重要。针对该问题,提出一种基于CFDs规则的快速判定修复序列的计算方法。首先,设计了一种数据修复框架。然后,利用CFDs之间的关联关系,提出了修复序列图的概念,以用于CFDs修复顺序的计算。一方面,可以避免某些错误的或者不必要的数据修复,提高修复的准确性。另一方面,使用规则来判定修复顺序比使用实际数据进行判定更为快速。此外,在判定修复序列的过程中,对修复死锁进行了检测,保证了修复过程的可终止性。最后,通过在真实数据集上与现有方法进行对比实验,证明了所提方法具有更高的准确性和运行效率。

Data consistency is one central issue of big data quality management research.Conditional functional dependencies(CFDs)are effective techniques for maintaining data consistency.In practice,different repairing sequences may affect precision and efficiency of data repairing.It is critical to select an appropriate repairing sequence.To solve the problem,based on CFDs,this paper presented a rapid decision method for repairing sequence.Firstly,a framework is designed for consistency repairing.Then,by analyzing the association between constraints,the concept of repairing sequence graph is presented to determine repairing sequence on CFDs.It contributes to avoiding some incorrect and unnecessary repairs,which can improve the accuracy of repairing.Meanwhile,repairing sequence with rules runs faster than that with real data.Furthermore,in the process of repairing sequence decision,repairing-deadlock detection is implemented to ensure the termination of repairing.Finally,compared with the existing method,this solution is more accurate and efficient evidenced by the empirical evaluation on two real-life datasets.