As data explosion grows, data quality issues become more and more concerned. Data timeliness as an important data quality property plays a key role in data mining. In the absence of timestamps, based on chronological order Association rules can better repair data, while conditional function dependence is a semantic complement to function dependencies, and it is widely used in database consistency repair. The general algorithm framework for timeliness and consistency repair in data quality is studied. Firstly, the definition of state timeliness rules and the mining algorithm of conditional function dependence are clarified. Then, based on the state type timeliness rules, the data is missing and error repaired in the case of timestamp missing, and then the conditional function is used to repair the data consistency. Finally, the algorithm is performed. The implementation and verification of the algorithm-related parameters on the real data set, the test success rate is tested and verified. The repair results have higher success rate and significant effect, and have application value in timeliness and consistency repair.
