一种用户频繁移动模式并行挖掘算法

针对用户的日常移动轨迹进行挖掘，可以有效地发现隐藏在用户生活中频繁出现的移动规律，即用户频繁移动模式,提出了一种基于PrefixSpan算法的用户频繁移动模式并行挖掘算法PASFORM.该算法利用了新的剪枝策略，缩小了搜索空间;引入了时间约束，挖掘出的频繁移动模式带有时间属性；使用前缀树存储频繁移动模式，缩小了存储空间；采用了并行化方法，适用于海量时空数据的挖掘.实验结果表明，该方法能够快速有效地挖掘出用户频繁移动模式.
Abstract：Through daily moving trajectories, one can effectively find the frequent moving rules, i.e., user frequent moving patterns. Based on PrefixSpan algorithm, a parallel algorithm named PASFORM is presented for mining user frequent moving patterns. PASFORM uses a new pruning strategy to reduce the search space and several time constraints to make mining results time-tagged. It also employs the parallel method to mine mass data and a prefix tree to save the store space. Experimental results show that PASFORM is effective and efficient.