Large knowledge graphs combine human knowledge garnered from projects ranging from academia and institutions to enterprises and crowdsourcing. Within such graphs, each relationship between two nodes represents a basic fact involving these two entities. The diversity of the semantics of relationships constitutes the richness of knowledge graphs, leading to the emergence of singular topologies, sometimes chaotic in appearance. However, this complex characteristic can be modeled in a simple way by introducing the concept of superficiality, which controls the overlap between relationships whose facts are generated independently. With this model, superficiality also regulates the balance of the global distribution of knowledge by determining the proportion of misdescribed entities. This is the first model for the structure and dynamics of knowledge graphs. It leads to a better understanding of formal knowledge acquisition and organization.

翻译：大型知识图谱整合了从学术机构、企业项目到众包活动等多种渠道获取的人类知识。在此类图谱中，任意两个节点间的关系代表涉及这两个实体的基本事实。关系语义的多样性构成了知识图谱的丰富性，催生了独特的拓扑结构，其表象有时呈现混沌特征。然而，通过引入表面性概念——该概念控制着由独立生成的事实所构成的关系间的重叠程度——这种复杂特性得以用简单方式建模。在此模型中，表面性还通过决定错误描述实体的比例，调控着知识全局分布的平衡性。这是首个针对知识图谱结构与动力学的模型，为形式化知识的获取与组织机制提供了更深入的理解。