Abstract:

As a classical association rule mining algorithm,Apriori scans the database repeatedly and has a large amount of connection times before the generation of candidate item sets,and a huge number of candidate item sets are generated.These defects result in low efficiency.An improved algorithm is proposed,which works in the following two steps.Firstly,some special affairs are deleted to reduce the times of scanning data.Secondly,the frequent k-1 item sets are reduced before generating candidate k-item sets,so the times of the frequent k-1 item sets connection and the number of candidate k item sets is reduced.Finally the improved Apriori algorithm is used in the analysis of the item relation of an examination to find the relationship among various questions.Experiments show that the improved algorithm is superior to Apriori algorithm in efficiency,and can get a good result.

Key words: association rule;the Apriori algorithm;frequent itemsets;efficiency;item analysis