An Efficient Distributed Algorithm for Mining Association Rules

Modern organizations are geographically distributed. Using the traditional centralized association rule mining to discover useful patterns in such distributed system is not always feasible because merging data sets from different sites into a centralized site incurs huge network communication and time costs. This paper presents an efficient distributed association rule mining (ED-ARM) algorithm to fast find the large itemsets over the distributed transaction database system. Our performance study shows that ED-ARM has a superior performance over the algorithms of CD and FDM.