Rule-based data relative aging repair and anomaly detection method

Data timeliness is an attribute reflecting data time characteristics and has an important influence on data quality and value. Once the time stamp of the data is lost or tampered, absolute accurate repair is difficult to carry out. Based on some rule rules, the data relative timeliness is repaired, and it is feasible to meet the requirements of data quality and data mining for the data timing sequence relation. On the basis of data aging rule related research, basic aging rules are expanded, and parallel extraction and incremental updating of the rules are realized; in order to solve the problems and requirements encountered in data aging repair, a rule-based data relative aging repair and anomaly detection method is provided, a measurement model for evaluating a repair result is established, and meanwhile, a method for detecting aging anomaly data by applying data aging repair is discussed. Experimental results and analysis show that the extended aging rule is feasible and available,and data timing sequence