Updating of association rules dynamically

We propose a new algorithm to handle the problem of updating of association rules. Recent methods on this problem usually employ the Apriori algorithm. We develop a new algorithm, called the incremental dynamic itemset counting algorithm. It makes use of the dynamic counting technique to deal with this problem in a more efficient way. Experimental results show that our new algorithm outperforms a recent incremental association rule mining algorithm in terms of the computational time. We also investigate a variant of our algorithm and demonstrate its effectiveness.