Abstract

Aim at resolving the problem of repeatedly accessing the database for mining association rule, this paper analyses the relation between rough set and association rule, then proposes a multi-dimensional association algorithm based on equivalence class in rough set. In this algorithm, the computing of multi-dimensional frequent items is converted to computing of equivalence class with multi-attributes. So, the number and content of multi-dimensional frequent items and association rules produced by this algorithm are limited by interesting dimensions which are assigned by user. Compared with Apriori algorithm, this algorithm reduces the number of accessing and scanning database. So this algorithm decreases the time of computing association rules and is efficient.

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