计算机应用与软件2011，Vol.28Issue(10)：34-37,4.
基于R-tree的高效异常轨迹检测算法
EFFICIENT OUTLIER DETECTION ALGORITHM FOR TRAJECTORY BASED ON R-TREE
摘要
Abstract
Outlier detection is a popular data mining task. However, there is a lack of serious study on outlier detection for trajectory data, and the existing algorithms also have the limitations. So J. -C Lee et al proposed TRAOD. TRAOD can effectively detect the abnormal trajectory, but it also has the defects. It is difficult to balance the accuracy and the complexity, the parameter selection is a little bit difficult too, the algorithm needs a long time to execute. Based on TRAOD's problems, this paper proposes the R-TRAOD, it is an efficient outlier detection algorithm based on R-tree trajectory. The algorithm indexes the trajectory points through R-tree for searching the trajectory points within the territory of their domain, then according to TRAOD it detects the abnormal trajectory against the trajectory points indexed by R-tree. In this way the operation speed of the algorithm can be improved. The test of real data experiments shows that this algorithm has higher efficiency than the latest TRAOD abnormal trajectory mining algorithm.关键词
R-tree/异常轨迹检测/TRAODKey words
R-tree/Abnormal trajectory detection/TRAOD分类
信息技术与安全科学引用本文复制引用
陈锦阳,刘良旭,宋加涛,王让定,管博..基于R-tree的高效异常轨迹检测算法[J].计算机应用与软件,2011,28(10):34-37,4.基金项目
国家自然科学基金(60972163) （60972163）
宁波市自然科学基金(2009A610090). （2009A610090）
