Method for mining and efficiently updating association rulesbased on item sets knowledge database

Mining association rules in transaction database is an important aspect of data mining field. Although several algorithms have been proposed for mining and updating association rules recently. However these algorithms have to scan a large database many times and a large quantity of I/Os for scanning lowered the efficiency to solve this problem, a method for mining and updating efficiently association rules based on itemsets knowledge database is provided. The proposed method only needs scanning a database one time to create an itemsets knowledge database comparing with the existing algorithms and this new method is more efficient and can be used not only in the case that the data are not changed while the mining support and confidence given by users are changed, but also in the case that the data in a transaction database are changed and the method is especially applied to the updating association rules interactively and is of practical use.