针对传统XML文档小枝模式查询算法中,与模式树中标签名相同的节点均入内存,易造成很大的空间浪费问题,提出了一种新的算法—StreamFWM(StreamFilter Without Merging)。StreamFWM采用区间编码方式,依据节点间的结构关系过滤标签流中无用的中间节点,且不用归并,只用简单的栈和列表实现。实验结果证明,算法StreamFWM相比TwigStack在查询处理的性能上有所提高。
With the development of global position system（GPS）,wireless technology and location aware services,it is possible to collect a large quantity of trajectory data.In the field of data mining for moving objects,the problem of anomaly detection is a hot topic.Based on the development of anomalous trajectory detection of moving objects,this paper introduces the classical trajectory outlier detection（TRAOD） algorithm,and then proposes a density-based trajectory outlier detection（DBTOD） algorithm,which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense.The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented,which show the effectiveness of the algorithm.
