Statistical Schema Induction

被引:0
|
作者
Voelker, Johanna [1 ]
Niepert, Mathias [1 ]
机构
[1] Univ Mannheim, KR & KM Res Grp, D-6800 Mannheim 1, Germany
关键词
Linked Data; Ontologies; Association Rule Mining; SEMANTIC WEB; KNOWLEDGE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
While the realization of the Semantic Web as once envisioned by Tim Berners-Lee remains in a distant future, the Web of Data has already become a reality. Billions of RDF statements on the Internet, facts about a variety of different domains, are ready to be used by semantic applications. Some of these applications, however, crucially hinge on the availability of expressive schemas suitable for logical inference that yields non-trivial conclusions. In this paper, we present a statistical approach to the induction of expressive schemas from large RDF repositories. We describe in detail the implementation of this approach and report on an evaluation that we conducted using several data sets including DBpedia.
引用
收藏
页码:124 / 138
页数:15
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