An Algorithm Research for Distributed Association Rules Mining with Constraints Based on Sampling

摘要

An algorithm for distributed mining association rules with constraints called DMCASE is presented using Sampling and constraint-based Eclat algorithm. At each database site, sampling algorithm and constraint-based Eclat algorithm are implemented. And the local frequent itemsets satisfying constraints are developed. They then are combined to global frequent itemsets satisfying constraints based on inductive learning method. DMCASE algorithm scans the whole database only once. It is also an algorithm with high efficiency. Results from our experiments show that the algorithm is an effective way to resolve the problem of distributed mining association rules with constraints