一个基于兴趣度的关联规则采掘算法

关联规则是当前数据采掘研究的主要领域之一,获取具有更高价值的规则是该领域的一个研究重点,针对目前大多数采掘算法只能发现正项的关联规则和仅仅将兴趣度作为规则过滤工具的问题,在先前研究的基础上,提出了通过改进有关定义和引进反向项集的概念来进一步发现包含负项的关联规则的思想,并给出了相应的算法,最后,对这个算法给出了一定的评价和实例分析。

A MINING ALGORITHM FOR ASSOCIATION RULES BASED ON INTEREST MEASURE

Association rules is one of the main research fields in data mining, and to gain the more valuable rules is a focus in this field. But most of the most current algorithms can only find out the positive-item rules and the interest measure can only be used as a filter. To solve this problem, an idea to find out the negative-item-contained rules is forword put through modification of the related definition and through the introduction of the negative itemset, based on the previous work. The algorithm based on this idea is also given. Finally, the algorithm is evaluated and analyzed through experiments and practices.