用于记录链接的数据驱动的名称缩减

Second International Conference on the Innovative Computing Technology (INTECH 2012) Pub Date : 2012-09-01 DOI:10.1109/INTECH.2012.6457783

M. Schraagen, W. Kosters

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引用次数: 2

摘要

在存在姓名变异和拼写错误的情况下，人名数据的自动记录链接是困难的。本文提出了一个人名的标准化程序，以解决人名的变异问题。使用65002个名称变体对的训练集构建基于分类树的模型。该方法为记录链接提供了一个有效的程序(每秒3500条记录，F-measure在荷兰历史民事记录样本上为0.96)。结果包括记录之间具有较大编辑距离的链接，但是这一类别的召回率较低。一个引导程序被用来提高召回率。

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Data-driven name reduction for record linkage

Automatic record linkage of data containing personal names is difficult in the presence of name variation and spelling errors. This paper presents a standardization procedure for personal names to address the variation problem. A classification tree based model is constructed using a training set of 65,002 name-variant pairs. The method provides an efficient procedure for record linkage (3500 records per second, F-measure 0.96 on a sample of Dutch historical civil records). The results include links with large edit distance between the records, however recall is lower for this category. A bootstrapping procedure is used to improve recall.

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Second International Conference on the Innovative Computing Technology (INTECH 2012)

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