一种用于移动计算的约束频繁邻近类别集挖掘算法

An algorithm of constraint frequent neighboring class sets mining in mobile computing

在移动计算中挖掘满足用户需求的长频繁邻近类别集时,为了避免产生冗余候选项和减少重复计算量,提出一种基于幂集数递减的约束频繁邻近类别集挖掘算法,其能够提取包含约束条件的长频繁邻近类别集;该算法用幂集数递减序列来产生候选频繁邻近类别集,有效地删除了不满足用户需求的冗余候选项和减少了重复扫描空间实例的计算量.实验表明在挖掘满足用户需求的长频繁邻近类别集时,该算法比现有算法更快速.

When mining long frequent neighboring class sets to meet user demand in mobile computing,in order to avoid creating redundancy candidate and reduce repeated calculated amount,this paper proposes an algorithm of constraint frequent neighboring class sets mining based on Power set number decreasing,which can extract long frequent neighboring class sets with constraint condition.The algorithm uses Power set decreasing sequence to create candidate frequent neighboring class sets,and deletes efficiently redundancy candidate to not meet user demand,and reduces these calculated amount of repeated scanning spatial instance.The experiment indicates that the algorithm is faster than present algorithm when mining long frequent neighboring class sets to meet user demand.