此处非彼处：面向位置隐私保护及其他应用的基于蕴含关系的轨迹相似性度量
Here Is Not There: Measuring Entailment-Based Trajectory Similarity for Location-Privacy Protection and Beyond
AI总结：
本文提出一种基于逻辑蕴含的轨迹相似性度量方法，通过计算空间关系事实的重叠比例来评估轨迹，并利用该方法评估隐私保护轨迹生成模型LSTM-TrajGAN，揭示了忽视地理空间结构可能带来的实际后果，为位置隐私保护等领域提供了新的推理视角。
摘要：
虽然人类行走的路径同时在社会空间和物理空间中展开，但描述和比较其轨迹的度量方法却是在抽象的、通常是欧几里得的空间中进行的。当这些度量被应用于实际个体的轨迹时，在抽象空间中无关紧要的改变一旦叠加到地理现实之上，就可能突然变得有问题。在这项工作中，我们通过引入一种利用逻辑蕴含的度量方法，提出了看待轨迹相似性的不同视角。这是一种推理性的视角，将事实视为从旅行发生的社会和环境背景中推导出的三元组陈述及其实际含义。我们提出了基于蕴含的轨迹相似性的形式化定义，其度量方式为事实的重叠比例，在我们的案例研究中这些事实是空间关系陈述。利用所提出的度量，我们评估了LSTM-TrajGAN，一种保护隐私的轨迹生成模型。基于蕴含的模型评估揭示了忽视地理空间丰富结构可能带来的后果（例如，在我们的玩具示例中，由于区域偏移导致的保险风险误算）。我们的工作凸显了将逻辑蕴含应用于轨迹相似性推理在位置隐私保护及其他领域的优势。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
