Distributed association rules mining algorithm by sampling and meta-learning
利用抽样技术和元学习的分布式关联规则挖掘算法

A new distributed association rule mining algorithm of DASM was presented. It adopted the ideas of dynamic itemset counting and sampling, and produced frequent itemsets by meta-learning method. Different sites that applied DASM needn't share the same memory. To assure the completeness of the results, the concept of similar degree was introduced. Theory analysis and experiments on the datasets generated using the generator from the IBM Almaden Quest research group show that DASM has better performance and less communication loads. DASM is applicable to those applications where the efficiency could be more important than accuracy results.performance and less communication loads. DASM is applicable to those applications where the efficiency could be more important than accuracy results.