论文标题
居住历史推断问题
The Residence History Inference Problem
论文作者
论文摘要
近年来,在线用户痕迹用于研究人类流动性。这种日益增长的工作体系,以及人类移民模式对政府和工业的更一般重要性,激发了对人类流动性的计算建模的必要性,尤其是个人如何以及何时从在线痕迹中改变其居住地。关于此主题的先前工作已经绕过了居住推论的基本计算建模,重点是迁移模式本身。因此,据我们所知,所有先前的工作都采用启发式方法来计算居住历史之类的东西。在这里,我们正式化了居住分配问题,该问题在与住所的最小住宿相关的限制下寻求,这是居住时期的最简约序列和解释个人运动历史的地方。在这里,我们为此问题提供了一个精确的解决方案,并建立了其算法复杂性。由于最佳居住历史记录的计算(在模型的假设下)是可以处理的,因此我们认为,该方法将是该主题将来工作的宝贵工具。
The use of online user traces for studies of human mobility has received significant attention in recent years. This growing body of work, and the more general importance of human migration patterns to government and industry, motivates the need for a formalized approach to the computational modeling of human mobility - in particular how and when individuals change their place of residence - from online traces. Prior work on this topic has skirted the underlying computational modeling of residence inference, focusing on migration patterns themselves. As a result, to our knowledge, all prior work has employed heuristics to compute something like residence histories. Here, we formalize the residence assignment problem, which seeks, under constraints associated with the minimum length-of-stay at a residence, the most parsimonious sequence of residence periods and places that explains the movement history of an individual. Here we provide an exact solution for this problem and establish its algorithmic complexity. Because the calculation of optimal residence histories (under the assumptions of the model) is tractable, we believe that this method will be a valuable tool for future work on this topic.