An improved algorithm for Mining Association Rule in relational database

This paper focuses the concept of data mining and association rules mining algorithm. Apriori algorithm and FP-growth algorithm, which are well-known and important data mining algorithms, are studied. According to the Apriori algorithm for weighted multidimensional data mining, this paper provides an optimized method which searches the candidate itemsets avoiding to scan the database repeatedly in order to improve the efficiency of data mining. The rule analysis on the achievement of senior students of a certain middle school is used for evaluation of the algorithm.