一种基于编码的关联规则挖掘算法

An Association Rule Mining Algorithm Based on Code

关联规则挖掘算法Apriori算法在挖掘频繁模式时需要产生大量的候选项集,多次扫描数据库,时空复杂度过高。针对该算法的局限性,提出了一种通过对项编码来减少扫描数据库次数并通过删除项来减少候选项集的数量,从而提高算法的效率。相同条件下的实验结果表明,优化后的算法能有效地提高关联规则挖掘的效率。

The most typical association rule mining algorithm is Apriori. In the process of mining frequent patterns,Apriori algorithm generates a huge number of candidate itemsets as well as needs multiple scans over database. So the time and space complexity is too high. According to the existing flaws of Apriori algorithm, propose an improved algorithm means of coding for every it^n. Coding can reduce the scans over database and meanwhile deleting items can reduce the number of candidate items. As a result, the efficiency of this algorithm has been imporved. Experiment done under the same conditions show that the advanced algorithm can effectively improve the efficiency of association rules mining.