摘要：

现行的移动目标行为规律侧重于空间或时间单一维度,且多集中于单移动目标的自身行为。为发现移动目标的关联共现规律,在传统轨迹序贯模式挖掘的基础上,基于常用的时间戳和地点的关联模型,加入任务属性信息,以移动目标在空间上的共同出现模式为基准分析时间上 的频繁度,提出一种将序列模式和关联规则应用到移动目标活动数据中的模式挖掘算法。实验结果证明,该算法能有效挖掘移动目标的活动地点关联性及协同共现规律,并且具有较低的算法复杂度,可以为建立移动目标的反应机制提供辅助决策。

关键词: 共现规律, 数据挖掘, 关联规则, 序列挖掘, 移动目标

Abstract:

The current mobile target behavioral rules mostly focus on the single dimension of space or time,or the self-behavior of a single moving target.In order to find out the association co-occurrence rule of moving targets,based on the traditional trajectory sequential pattern mining,this paper adds task attribute information with commonly used time stamps and place association models,and then takes the co-occurrence pattern of moving objects in space as a benchmark to further analyze the frequency of time,proposes a pattern mining algorithm which applies the association rule and sequence mining to the location and equipment association data of the moving target.Experimental results prove that this algorithm can effectively mine the activity location correlation and the rule of co-occurrence of moving target,and has lower algorithm complexity,which can provide decision-making for the establishment of the reaction mechanism of the moving target.

Key words: co-occurrence rule, data mining, association rule, sequence mining, moving target

中图分类号: 

• TP301.6