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Graph summarization for source selection of querying over Linked Open Data

机译:图形汇总,用于通过链接的开放数据进行查询的源选择

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摘要

How to query Linked Open Data effectively is a challenge due to large amounts of distributed datasets and lacking of overall information about it. Source selection that filters query-relevant datasets is a challenge. We propose a graph structure named `Predicate Line Graph (PLG)' to summarize dataset by using schema-level information, and then interlink different PLGs to build a global summarization by using schema-level or instance-level mapping information. In experiments, the global view is generated by Linked Open Data sets and then it is evaluated by query sets. The experimental results show that our summarization can select candidate datasets effectively.
机译:由于大量的分布式数据集和缺乏有关它的整体信息,如何有效地查询链接的开放数据是一个挑战。筛选与查询相关的数据集的源选择是一个挑战。我们提出一种名为“谓词折线图(PLG)”的图结构,以使用模式级信息汇总数据集,然后使用模式级或实例级映射信息将不同的PLG互连以建立全局汇总。在实验中,全局视图由链接的开放数据集生成,然后由查询集评估。实验结果表明,本文的总结可以有效地选择候选数据集。

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