摘要
针对基于频繁项集的关联规则挖掘算法效率低,需要多次扫描数据库且生成冗余候选项集问题,该文利用频繁项集的Aprior性质和概念格的基本思想提出一种关联规则提取算法,利用极大频繁项集来进行规则提取,去除了多数冗余的候选项集,提高了提取效率。
Association rules mining is an important research branch in data mining. However, most algorithms based on frequent item sets have to scan databases many times, which reduces extraction efficiency. This paper presents an algorithm to find all maximal frequent item sets quickly. The algorithm is based on concept lattice and it can certify all frequent item sets efficiently, which avoids calculating the redundant item sets and improves the extraction efficiency.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第5期63-65,共3页
Computer Engineering
关键词
关联规则
数据挖掘
频繁项集
概念格
提取
association rules
data mining
frequent item sets
concept lattice
extraction
