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Assessing Linked Data Mappings Using Network Measures

机译:使用网络量度评估链接的数据映射

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Linked Data is at its core about the setting of links between resources. Links provide enriched semantics, pointers to extra information and enable the merging of data sets. However, as the amount of Linked Data has grown, there has been the need to automate the creation of links and such automated approaches can create low-quality links or unsuitable network structures. In particular, it is difficult to know whether the links introduced improve or diminish the quality of Linked Data. In this paper, we present LINK-QA, an extensible framework that allows for the assessment of Linked Data mappings using network metrics. We test five metrics using this framework on a set of known good and bad links generated by a common mapping system, and show the behaviour of those metrics.
机译:链接数据的核心是资源之间的链接设置。链接提供了丰富的语义,指向额外信息的指针,并实现了数据集的合并。但是,随着链接数据量的增长,需要自动创建链接,而这种自动化方法可能会创建低质量的链接或不合适的网络结构。特别是,很难知道引入的链接是提高还是降低了链接数据的质量。在本文中,我们介绍了LINK-QA,这是一个可扩展的框架,允许使用网络指标评估链接的数据映射。我们使用此框架在由公共映射系统生成的一组已知的好和坏链接上测试了五个指标,并显示了这些指标的行为。

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