摘要
文章研究了一种知识发现与数据挖掘中关联规则的发现方法。针对现有大型超市销售事务数据库 ,提出了一种新的多层次信息获取方法。运用关联规则挖掘所产生的频繁集对数据压缩表示 ,并给出了按用户的实际需求交互式挖掘感兴趣关联规则的算法。该算法在挖掘速度和效率上有较大提高。
A novel algorithm to discover association rules in Knowledge Discovery and Data Mining is presented. According to the current large-scale supermarket transaction data set, a new multiple-level taxonomy is proposed. The frequent itemsets obtained when identifying association rules can be used to compress the data set. Then, an algorithm, which is based on the frequent itemsets, ispresented to find the interesting rules interactively with the users' practicalneeds.Therefore, mining process and efficiency are greatly improved.
出处
《微电子学与计算机》
CSCD
北大核心
2000年第3期54-58,共5页
Microelectronics & Computer
基金
国家自然科学基金!(69835010)
关键词
频繁集
多层次信息
关联规则
数据挖掘
数据库
Frequent itemset,Multiple-level taxonomy,Interactive,Association rules
