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首页> 外文期刊>Vietnam Journal of Computer Science >Storing Hypergraph-Based Data Models in Non-Hypergraph Data Storage and Applications for Information Systems
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Storing Hypergraph-Based Data Models in Non-Hypergraph Data Storage and Applications for Information Systems

机译：在非超图数据存储和应用程序中存储基于超图数据模型的信息系统

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Data structures and especially the relationship among the data entities have changed in the last couple of years. The network-like graph representations of data-model are becoming more and more common nowadays, since they are more suitable to depict these, than the well-established relational data-model. The graphs can describe large and complex networks — like social networks — but also capable of storing rich information about complex data. This was mostly of relational data-model trait before. This also can be achieved with the use of the knowledge representation tool called “hypergraphs”. To utilize the possibilities of this model, we need a practical way to store and process hypergraphs. In this paper, we propose a way by which we can store hypergraphs model in the SAP HANA in-memory database system which has a “Graph Core” engine besides the relational data model. Graph Core has many graph algorithms by default however it is not capable to store or to work with hypergraphs neither are any of these algorithms specifically tailored for hypergraphs either. Hence in this paper, besides the case study of the two information systems, we also propose pseudo-code level algorithms to accommodate hypergraph semantics to process our IS model.
机译：数据结构尤其是数据实体之间的关系在过去几年中发生了变化。数据模型的网络状图表表示现在变得越来越普遍，因为它们更适合描述这些，而不是建立了良好的关系数据模型。图表可以描述大型和复杂的网络 - 类似的社交网络 - 但也能够存储有关复杂数据的丰富信息。这主要是以前的关系数据模型特征。这也可以通过使用称为“超图”的知识表示工具来实现。要利用此模型的可能性，我们需要一种存储和处理超图的实用方法。在本文中，我们提出了一种方法，我们可以通过它在内存数据库系统中存储超图模型，除了关系数据模型之外。图形核心默认有许多图形算法，但它无法存储或使用超图工作，这些算法也不专门针对超图量身定制。因此，在本文中，除了两个信息系统的案例研究之外，我们还提出了伪码级算法，以适应超图语义来处理我们的模型。

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