Mining decision rules based on the improved Apriori algorithm

The wide range application of the computer accumulated vast amounts of data.Data mining can extracted the implied,unknown,and the potential value of information or patterns from large database or data warehouse.Association rules is one of the most active branch of data mining,focusing on mining the deep-level relationship among data items in the database,and analyzing the potential behavior patterns.Apriori algorithm is the most classical algorithm for mining association rules.This paper introduced the basic method of Apriori algorithm,and changed it in three aspects: data item establishment,frequent item sets connection and the rule generation.Using the changed algorithm,mined rules can be used for decision-making.