Optimization of Association Rule Learning in Distributed Database using Clustering Technique
Association rule mining is a way to find interesting associations among different large sets of data item. Apriori is the best known algorithm to mine the association rules. In this paper, clustering technique is used to improve the computational time of mining association rules in databases using access data. Clusters are used to improve the performance of computer. Clusters are responsible for finding the frequent k item sets; hence lot of work is performed in parallel, thus decreasing the computation time.