Title :
Efficient mining of association rules in distributed databases
Author :
Cheung, David W. ; Ng, Vincent T. ; Fu, Ada W. ; Yongjian Fu
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ., Hong Kong
fDate :
12/1/1996 12:00:00 AM
Abstract :
Many sequential algorithms have been proposed for the 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 effective, because it requires a large amount of communication overhead. In this study, an efficient algorithm called DMA (Distributed Mining of Association rules), 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 testbed, and its performance is studied. The results show that DMA has superior performance, when compared with the direct application of a popular sequential algorithm, in distributed databases
Keywords :
communication complexity; database theory; deductive databases; distributed algorithms; distributed databases; knowledge acquisition; DMA algorithm; association rules; candidate sets; communication overhead; distributed algorithm; distributed data mining; distributed databases; knowledge discovery; messages; partitioned database; performance; support-count exchange; Association rules; Computer science; Data mining; Distributed algorithms; Distributed databases; Economic forecasting; Partitioning algorithms; Testing; Transaction databases; Warehousing;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
