Improvement of AprioriTid Algorithm for Mining Association Rules
Shuangying Liu · Journal of Yantai University · 2003
Mining association rule is one of the common forms in data mining, in which the critical problem is to get the frequent itemsets efficiently. AprioriTid algorithm, which is used to construct the frequent itemset, is analyzed in the paper. Based on the analysis, the defect is pointed out that there are too many data due to those items repeatedly saved in the algorithm, and the theorem of the itemset whose support is less than minsupport in Ck-1 is useless in Ck-l is put forward and proved. And then a new algorithm based the theorem is offered. Experiments show that the new algorithm is effective in decreasing data size.