论文标题
分类空间轨迹
Classifying Spatial Trajectories
论文作者
论文摘要
我们提供了有关如何仅使用其空间表示形式对轨迹进行分类的首次综合研究，该研究仅在5个现实世界数据集上测量。我们的比较考虑了20个不同的分类器，它们是流行距离的KNN分类器，或使用每个轨迹的矢量化表示形式作为更通用的分类器。我们还开发了如何通过数据驱动的方法来选择相关地标的矢量化轨迹的新方法，这些方法证明是我们研究中最有效的方法之一。这些矢量化方法可简单且有效地使用，并且在既定的运输模式分类任务上也提供了最先进的准确性。总的来说，这项研究为如何对轨迹进行分类奠定了标准，包括引入新的简单技术来实现这些结果，并为不可避免的对此主题的未来研究设定了严格的标准。
We provide the first comprehensive study on how to classify trajectories using only their spatial representations, measured on 5 real-world data sets. Our comparison considers 20 distinct classifiers arising either as a KNN classifier of a popular distance, or as a more general type of classifier using a vectorized representation of each trajectory. We additionally develop new methods for how to vectorize trajectories via a data-driven method to select the associated landmarks, and these methods prove among the most effective in our study. These vectorized approaches are simple and efficient to use, and also provide state-of-the-art accuracy on an established transportation mode classification task. In all, this study sets the standard for how to classify trajectories, including introducing new simple techniques to achieve these results, and sets a rigorous standard for the inevitable future study on this topic.
