计算机工程2012，Vol.38Issue(4)：73-75,3.
项约束先过滤的最大频繁项集挖掘算法
Mining Algorithm of Maximal Frequent Itemset with Item Constraint Filtering First
姚全珠 1李如琼 1王美君1
作者信息
- 1. 西安理工大学计算机科学与工程学院,西安710048
- 折叠
摘要
Abstract
In the dense database, mining maximal frequent itemsets takes too much time, and the results are too large to satisfy the users. This paper proposes a maximal frequent itemsets mining algorithm, called VCM. It filters the database with the constraints, uses the vertical data representation of data sets and adopts depth-first strategy for mining maximum frequent itemsets. Compared with other algorithms, experimental results show that the VCM algorithm is faster and more effective, and the advantage is remarkable when the databases are dense and with long patterns.关键词
关联规则/最大频繁项集/项约束/垂直数据格式/深度优先/稠密数据库Key words
association rule/ maximal frequent itemset/ item constraint/ vertical data format/ depth-first/ dense database分类
信息技术与安全科学引用本文复制引用
姚全珠,李如琼,王美君..项约束先过滤的最大频繁项集挖掘算法[J].计算机工程,2012,38(4):73-75,3.
