Linking the Thesaurus for the Social Sciences to the Web of Linked Data

Andias Wira-Alam, A. Kempf, Benjamin Zapilko
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Abstract

In this paper, we apply different methods for linking subject headings of the Thesaurus for the Social Sciences (TheSoz) to DBpedia, the nucleus of the Web of Linked Data which is derived from the structured information of Wikipedia. Our method utilizes the backlinks and outlinks within Wikipedia for link detection. We examine to what extent the linking process can be optimized with the help of a network-based similarity measure, in order to achieve a higher precision and recall. We test two baseline methods, string alignment and language property matching and compare them to our own method. Our method outperforms the F-scores of the baselines by 10 percentage points.
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将社会科学词典与关联数据网络连接起来
在本文中,我们应用不同的方法将社会科学同义词词典(TheSoz)的主题标题链接到DBpedia, DBpedia是源自维基百科结构化信息的关联数据网络的核心。我们的方法利用维基百科内的反向链接和外链接进行链接检测。我们研究了在多大程度上可以利用基于网络的相似性度量来优化链接过程,以达到更高的精度和召回率。我们测试了两个基线方法,字符串对齐和语言属性匹配,并将它们与我们自己的方法进行比较。我们的方法比基线的f分数高出10个百分点。
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