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Big data entity resolution: From highly to somehow similar entity descriptions in the Web

机译:大数据实体解析:从高度到某种程度上Web中相似的实体描述

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In the Web of data, entities are described by interlinked data rather than documents on the Web. In this work, we focus on entity resolution in the Web of data, i.e., identifying descriptions that refer to the same real-world entity. To reduce the required number of pairwise comparisons, methods for entity resolution perform blocking as a pre-processing step. A blocking technique places similar entity descriptions into blocks and executes comparisons only between descriptions within the same block. We experimentally evaluate blocking techniques proposed for the Web of data and present dataset characteristics that determine the effectiveness and efficiency of such methods. Furthermore, we analyze the characteristics of the missed matching entity descriptions and examine different types of links that blocking techniques can potentially identify.
机译:在数据Web中,实体是通过互连的数据而不是Web上的文档来描述的。在这项工作中,我们专注于数据网络中的实体解析,即识别引用同一真实世界实体的描述。为了减少所需的成对比较次数,用于实体解析的方法将阻塞作为预处理步骤来执行。阻塞技术将相似的实体描述放入块中,并且仅在同一块内的描述之间执行比较。我们通过实验评估为数据Web提出的阻塞技术,并确定确定此类方法的有效性和效率的数据集特征。此外,我们分析了错过的匹配实体描述的特征,并检查了阻塞技术可以识别的不同类型的链接。

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