Many sequential algorithms have been proposed for mining of association rules. However, very little work has been done in mining association rules in distributed databases. A direct application of sequential algorithms to distributed databases is not e ective, because it requires a large amount of communication overhead. In this study, an e cient algorithm, DMA, is proposed. It generates a small number of candidate 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 database. The algorithm has been implemented on an experimental test bed and its performance is studied. The results show that DMA has superior performance when comparing with the direct application of a popular sequential algorithm in distributed databases.
The mining of association rules in distributed data bases has been examined in REF .
Efficient Mining of Association Rules in Distributed Databases
IEEE Trans. Knowl. Data Eng.
Computer Science