While the paths humans take play out in social as well as physical space, measures to describe and compare their trajectories are carried out in abstract, typically Euclidean, space. When these measures are applied to trajectories of actual individuals in an application area, alterations that are inconsequential in abstract space may suddenly become problematic once overlaid with geographic reality. In this work, we present a different view on trajectory similarity by introducing a measure that utilizes logical entailment. This is an inferential perspective that considers facts as triple statements deduced from the social and environmental context in which the travel takes place, and their practical implications. We suggest a formalization of entailment-based trajectory similarity, measured as the overlapping proportion of facts, which are spatial relation statements in our case study. With the proposed measure, we evaluate LSTM-TrajGAN, a privacy-preserving trajectory-generation model. The entailment-based model evaluation reveals potential consequences of disregarding the rich structure of geographic space (e.g., miscalculated insurance risk due to regional shifts in our toy example). Our work highlights the advantage of applying logical entailment to trajectory-similarity reasoning for location-privacy protection and beyond.

中文翻译：

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这里不存在：测量基于蕴含的轨迹相似性以实现位置隐私保护及其他方面

虽然人类的路径在社会和物理空间中发挥作用，但描述和比较其轨迹的措施是在抽象的、通常是欧几里得空间中进行的。当这些措施应用于应用区域中实际个体的轨迹时，抽象空间中无关紧要的改变一旦与地理现实重叠，可能会突然变得有问题。在这项工作中，我们通过引入利用逻辑蕴涵的度量，提出了关于轨迹相似性的不同观点。这是一种推理视角，将事实视为从旅行发生的社会和环境背景及其实际含义中推导出来的三重陈述。我们建议将基于蕴涵的轨迹相似性形式化，以事实的重叠比例来衡量，这是我们案例研究中的空间关系陈述。通过所提出的措施，我们评估了 LSTM-TrajGAN，一种隐私保护轨迹生成模型。基于蕴涵的模型评估揭示了忽视地理空间丰富结构的潜在后果（例如，在我们的玩具示例中，由于区域变化而错误计算了保险风险）。我们的工作强调了将逻辑蕴涵应用于轨迹相似性推理以实现位置隐私保护等的优势。