基于图常量条件函数依赖的图修复规则发现OACSTPCD

Data consistency is an important part of data quality management.In order to improve graph data consistency,a lot of data de-pendency theories in relational database have been introduced into graph database,including graph functional dependencies,graph association rules and so on.Graph repairing rule is a newly proposed data dependency rule for graph with powerful repairing capability,but there is no effective mining algorithm yet.In order to automatically generate graph repairing rule and improve the reliability of graph data repairing,a method called GenGRR is proposed to transform graph constant conditional functional dependencies into graph repairing rules.By using the graph pattern,the isomorphic subgraph is matched and mapped into a node-attribute two-dimensional table,and the error pattern is extracted from the corresponding attribute field in the table to transform the constant condition function dependency into the graph attribute value repair rule.The graph attribute supplement rules are generated by deleting the nodes and contiguous edges of constant condition function dependent on RHS in graph mode.Based on the maximum common isomorphic subgraph,the consistency of the repair rules of the generated graph is screened and verified.It is tested on multiple real data sets to verify that the graph repair rule generated by transformation has better repair effect than that of the graph constant condition function.