一种基于向量的关联规则挖掘算法改进

Improvement of Association Rules Mining Aigorithm Based on Vector

通过对Apriori算法思想和传统的向量挖掘算法进行分析,提出一种基于向量运算的关联规则改进算法。该算法采用树形数据结构,克服了Apriori算法需多次扫描数据库这一缺点,并通过向量计算来避免生成候选项集,经过实验证明提高了关联规则挖掘的效率。

Through the analisis on the Aprior algorithm and traditional vector mining algorithms, the article presents a imporvement of association rules algorithm based on vector, which applies tree data structure and has overcome the shortcoming of Apriori algorithm which need to scan the database many times, avoids to generat candidate itemsets by vector calculation, the experimental results show it has enhanced the efficiency of the mining association rules.