基于随机游走者的时序接触图生成
Generating Temporal Contact Graphs Using Random Walkers
AI总结：
本研究针对人类移动网络的时序接触图建模问题，提出RWIG模型，基于独立随机游走者生成时序接触图，经验证具真实性且可解析推导接触图分布闭式解，可媲美经典固定图模型。
摘要：
我们通过个体间接触的时间序列研究人类移动网络。我们提出的随机游走者诱导时序图（RWIG）模型，基于在离散时间步长中遍历底层图的独立随机游走者生成时序图序列。游走者在给定节点和时间的共在定义了个体层面的接触。研究表明，RWIG是时序人类接触图的真实模型，可与固定图的Erdos-Renyi（ER）模型和Barabasi-Albert（BA）模型相提并论。此外，RWIG具备解析可行性：我们推导了接触图概率分布的闭式解。
英文摘要：
We study human mobility networks through timeseries of contacts between individuals. Our proposed Random Walkers Induced temporal Graph (RWIG) model generates temporal graph sequences based on independent random walkers that traverse an underlying graph in discrete time steps. Co-location of walkers at a given node and time defines an individual-level contact. RWIG is shown to be a realistic model for temporal human contact graphs, which may place RWIG on a same footing as the Erdos-Renyi (ER) and Barabasi-Albert (BA) models for fixed graphs. Moreover, RWIG is analytically feasible: we derive closed form solutions for the probability distribution of contact graphs.
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。
