In recent years, the Graph Model has become increasingly popular, especially in the application domain of social networks. The model has been semantically augmented with properties and labels attached to the graph elements. It is difficult to ensure data quality for the properties and the data structure because the model does not need a schema. In this paper, we propose a schema bound Typed Graph Model with properties and labels. These enhancements improve not only data quality but also the quality of graph analysis. The power of this model is provided by using hyper-nodes and hyper-edges, which allows to present a data structure on different abstraction levels. We demonstrate by example the superiority of this model over the property graph data model of Hidders and other prevalent data models, namely the relational, object-oriented, and XML model.
翻译:近年来,图表模型越来越受欢迎,特别是在社交网络的应用领域,该模型在音义和标签上与图形元素相连接,因此难以确保属性和数据结构的数据质量,因为模型不需要模型。在本文中,我们提出了一个带有属性和标签的组合式图表模型。这些增强不仅提高了数据质量,也提高了图表分析的质量。该模型的力量通过使用超节点和高端来提供,从而可以展示不同抽象层次的数据结构。我们通过实例来证明这一模型优于希德斯的属性图表数据模型和其他流行的数据模型,即关联、对象导向和XML模型。