基于统计推理的不一致数据清洗方法OA北大核心CSTPCD

Inconsistent data repair is an important research direction in the field of data repair.Most of the existing methods are based on integrity constraint rules and use the principle of minimum cost for repair.However,the repair scheme with the minimum cost is usually incorrect,which leads to the low accuracy rate of the existing repair methods.To address the problem of low accuracy of existing methods,this paper proposed an inconsistent data repair method based on statistical inference BayesOUR,to balance the cost and quality of repair and improve the repair accuracy.It mainly divided BayesOUR into three phases.Firstly,it performed error detection based on the integrity constraint rule,and then utilized Bayesian network to reason about the probability of all the possible consistent repair schemes.Finally,it selected the repair scheme with the largest proba-bility for data repair.Experimental results on real data show that the method in this paper can significantly improve the accura-cy of inconsistent data repair compared with the current leading methods.