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DC Proposal: Towards Linked Data Assessment and Linking Temporal Facts

机译:DC建议:进行链接数据评估和链接时态

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Since the Linked Data is continuously growing on the Web, the quality of overall data can rapidly degrade over time. The research proposed here deals with the quality assessment in the Linked Data and the temporal linking techniques. First, we conduct an in-depth study of appropriate dimensions and their respectively metrics by denning a data quality framework that evaluates, along these dimensions, linked published data on the Web. Second, since the assessment and improvement of the Linked Data quality such as accuracy or the resolution of heterogeneities is performed through record linkage techniques, we propose an extended technique that apply time in similarity computation which can improve over traditional linkage techniques. This paper describes the core problem, presents the proposed approach, reports on initial results, and lists planned future tasks.
机译:由于链接数据在Web上不断增长,因此总体数据的质量会随着时间的推移而迅速下降。这里提出的研究涉及链接数据中的质量评估和时间链接技术。首先,我们通过定义一个数据质量框架对适当的维度及其各自的指标进行深入研究,该框架根据这些维度评估Web上已链接的已发布数据。其次,由于通过记录链接技术对链接数据质量(例如准确性或异质性分辨率)进行评估和改进,因此我们提出了一种扩展的技术,该技术将时间应用于相似度计算,可以比传统的链接技术有所改进。本文描述了核心问题,提出了建议的方法,报告了初步结果,并列出了计划中的未来任务。

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