An Improvement of Apriori Algorithm for Mining Association Rules

Association rule mining can find interesting associations among a large set of data items,and has been applied widely in many fields.But the importance of data items is seldom considered in the traditional association rules which think every data item has the same importance for rules,actually the result of mining is not good.To explore the more valuable rules,present weighted association rule algorithms that is to use frequentness and profit to express the importance,and then improve the classical Apriori algorithms.Finally use the example to testify the improved algorithms that is reasonable and find much more valuable information.