一种隐私保护的在线相似轨迹挖掘方法

Privacy aware online mining of similar trajectories

摘要:

为了解决相似轨迹挖掘中的隐私保护、轨迹数据简化和在线处理问题,提出了一种能够保护用户原始轨迹数据隐私的在线挖掘相似轨迹的方法．该方法首先利用随机投影技术压缩和扰动原始轨迹数据,然后通过基于密度的聚类方法判定各个时间段内相似的移动对象,采用局部敏感哈希技术寻找在足够多的时间段内都相似的移动对象,避免了传统方法中的交集运算,实现快速估计轨迹间相似度．实验结果表明: 该方法能够有效的发现相似轨迹,并且时间开销较小．

Abstract:

The problems of privacy preserving, trajectory data simplification and online processing attract considerable efforts from researchers in the area of trajectory data mining, unfortunately, it is difficult for traditional method to solve all these problems. This paper proposes an online similar trajectories mining method which can preserve the privacy of original trajectory data. The method first compressed and perturbed the original data based on random projection technique, then found the similar moving objects in each time segment by clustering the transformed data based on density, and finally it found similar trajectories by estimating that if the trajectories were similar for a long enough duration and estimated the similarity of trajectories using local sensitivity hashing. This avoided the intersection operation in traditional method and reduced the computation time. The experimental results show that this method can find similar trajectories effectively and reduce the cost of computation time. 