论文标题
社交网络的无分销模型
Distribution-Free Models of Social Networks
论文作者
论文摘要
大规模社交网络的结构主要使用生成模型（一种平均案例分析形式）来表达。本章调查了此类网络更强大模型的最新建议。这些模型假定确定性和经验支持的组合结构，而不是特定的概率分布。我们讨论了这些模型的形式定义，以及它们如何与社交网络中的经验观察以及相应图类别的已知结构和算法结果相关。
The structure of large-scale social networks has predominantly been articulated using generative models, a form of average-case analysis. This chapter surveys recent proposals of more robust models of such networks. These models posit deterministic and empirically supported combinatorial structure rather than a specific probability distribution. We discuss the formal definitions of these models and how they relate to empirical observations in social networks, as well as the known structural and algorithmic results for the corresponding graph classes.
