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Benchmarking Blocking Algorithms for Web Entities

机译:用于Web实体的基准阻塞算法

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摘要

An increasing number of entities are described by interlinked data rather than documents on the Web. Entity Resolution (ER) aims to identify descriptions of the same real-world entity within one or across knowledge bases in the Web of data. To reduce the required number of pairwise comparisons among descriptions, ER methods typically perform a pre-processing step, called blocking, which places similar entity descriptions into blocks and thus only compare descriptions within the same block. We experimentally evaluate several blocking methods proposed for the Web of data using real datasets, whose characteristics significantly impact their effectiveness and efficiency. The proposed experimental evaluation framework allows us to better understand the characteristics of the missed matching entity descriptions and contrast them with ground truth obtained from different kinds of relatedness links.
机译:越来越多的实体由互连的数据而不是网络上的文档来描述。实体分辨率(ER)旨在识别在数据WEB中的一个或跨越知识库中的相同现实世界实体的描述。为了减少描述之间所需的成对比较,ER方法通常执行称为阻塞的预处理步骤,其将相似的实体描述与块相似,因此仅在同一块内比较描述。我们通过实际数据集进行实验评估了为数据网提出的数据,其特征显着影响其有效性和效率。拟议的实验评估框架使我们能够更好地了解错过的匹配实体描述的特征,并以从不同类型的相关联系中获得的地面真理对比。

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