基于关联规则挖掘领域的Apriori算法的优化研究

Optimization of Apriori Algorithm in Mining Association Rules

挖掘关联规则是数据挖掘领域的一个重要研究课题,在挖掘数据间的关联性时具有非常重要的意义。本文在分析关联规则挖掘及Apriori算法的基础上,从压缩扫描数据集及提高剪枝效率等方面对算法进行了优化改进,从而达到了降低消耗、提高算法效率的目的。最后,通过实例对优化的Apriori算法作了详细介绍。

In the data mining field, mining association rules is an important topic in practical applications. On the basis of the Apriori algorithm, this paper proposes a new optimization method for scanning compressed data sets and improving the efficiency of the pruning step, in order to reduce consumption and improve the efficiency of algorithms. Finally, this paper gives an example in detail.