计算机工程2012，Vol.38Issue(11)：62-65,4.DOI:10.3969/j.issn.1000-3428.2012.11.020
依赖于约束幂集的频繁邻近类别集挖掘算法
Frequent Neighboring Class Set Mining Algorithm Depending on Constraint Power Set
摘要
Abstract
This paper proposes a constraint power set concept based on power set theory, and proposes an algorithm of mining frequent Neighboring Class Set(NCS) depending on constrain power set. The algorithm uses computing constraint power set mapping to generate candidate frequent NCS and computes its support count. It not only avoids generating redundant candidate, but also reduces calculation amount of repeated scanning database. Experimental result indicates that the algorithm is faster and more efficient than present mining algorithm when extracting constraint frequent NCS.关键词
邻近类别集/约束条件/幂集映射/约束幂集/空间关联规则/空间数据挖掘Key words
Neighboring Class Set(NCS)/ constraint condition/ power set mapping/ constraint power set/ spatial association rule/ spatial data mining分类
自科综合引用本文复制引用
方刚..依赖于约束幂集的频繁邻近类别集挖掘算法[J].计算机工程,2012,38(11):62-65,4.基金项目
重庆三峡学院科研基金资助重点项目(11ZD-18) （11ZD-18）
