Efficient mining of association rules in distributed databases 论文

1996IEEE Transactions on Knowledge and Data Engineering引用 346
Data Mining Algorithms and ApplicationsRough Sets and Fuzzy LogicAlgorithms and Data Compression

详细信息

发表期刊/会议
IEEE Transactions on Knowledge and Data Engineering
发表日期
1996-01-01
发表年份
1996

关键词

Data Mining Algorithms and ApplicationsRough Sets and Fuzzy LogicAlgorithms and Data Compression

摘要

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.