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Building XML Data Warehouse with Data Reconstruction by Knowledge Graph

机译:通过知识图重建数据来构建XML数据仓库

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The analysis and decision scenarios, which are more complex in many domains, request more unstructured data to be reorganized with the structured data for analyzing. An architecture is proposed in this paper for data reconstruction to support OLAP analysis based on the knowledge graph and XML data warehouse technologies. In this architecture, the data cubes can be built with the data of two kinds of knowledge graphs, and the data populating of the cubes is on the basis of the correlation of the entities in knowledge graphs. Under the consideration of utilizing both information of the ontology concepts and their entities, a modified module in the architecture is also proposed for good concept selection to extract the cube dimension hierarchies. The evolution results prove the effectiveness and advantages of our proposed architecture and modified module.
机译:在许多领域中更为复杂的分析和决策场景要求将更多的非结构化数据与结构化数据进行重组以进行分析。本文提出了一种基于知识图和XML数据仓库技术的数据重建架构,以支持OLAP分析。在这种体系结构中,可以使用两种知识图的数据来构建数据多维数据集,并且多维数据集的数据填充是基于知识图中实体的相关性。考虑到利用本体概念及其实体的信息,还提出了架构中的修改模块,以进行良好的概念选择,以提取多维数据集维度层次结构。演化结果证明了我们提出的体系结构和修改后的模块的有效性和优势。

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