EFFICIENT MINING OF ASSOCIATION RULES IN DISTRIBUTED DATABASES

Many sequential algorithms have been proposed for mining of associatio n rules. However, very little work has been done in mining association rules in distributed databases. A direct application of sequential al gorithms to distributed databases is not effective, because it require s a large amount of communication overhead. In this study, an efficien t algorithm, DMA, is proposed. It generates a small number of candidat e sets and requires only O(n) messages for support count exchange for each candidate set, where n is the number of sites in a distributed da tabase. The algorithm has been implemented on an experimental test bed and its performance is studied. The results show that DMA has superio r performance when comparing with the direct application of a popular sequential algorithm in distributed databases.