Visual querying is essential for interactively exploring massive trajectory data. However, the data uncertainty imposes profound challenges to fulfill advanced analytics requirements. On the one hand, many underlying data does not contain accurate geographic coordinates, e.g., positions of a mobile phone only refer to the regions (i.e., mobile cell stations) in which it resides, instead of accurate GPS coordinates. On the other hand, domain experts and general users prefer a natural way, such as using a natural language sentence, to access and analyze massive movement data. In this paper, we propose a visual analytics approach that can extract spatial-temporal constraints from a textual sentence and support an effective query method over uncertain mobile trajectory data. It is built up on encoding massive, spatially uncertain trajectories by the semantic information of the POls and regions covered by them, and then storing the trajectory documents in text database with an effective indexing scheme. The visual interface facilitates query condition specification, situation-aware visualization, and semantic exploration of large trajectory data. Usage scenarios on real-world human mobility datasets demonstrate the effectiveness of our approach.

中文翻译：

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基于自然语言的不确定人类轨迹的可视化查询方法。

可视查询对于交互式探索大量轨迹数据至关重要。但是，数据不确定性给满足高级分析要求提出了严峻的挑战。一方面，许多基础数据不包含准确的地理坐标，例如，移动电话的位置仅是指其所驻留的区域（即，移动小区站），而不是精确的GPS坐标。另一方面，领域专家和一般用户更喜欢自然的方式，例如使用自然的语言句子，来访问和分析大量的运动数据。在本文中，我们提出了一种视觉分析方法，该方法可以从文本句子中提取时空约束，并支持对不确定的移动轨迹数据进行有效的查询。它建立在大量编码的基础之上，利用POl及其覆盖区域的语义信息在空间上确定不确定的轨迹，然后使用有效的索引方案将轨迹文档存储在文本数据库中。可视界面有助于查询条件的指定，情况感知的可视化以及大型轨迹数据的语义探索。真实的人类机动性数据集上的使用场景证明了我们方法的有效性。