Mining the Web of Linked Data with RapidMiner

被引：49

作者：

Ristoski, Petar ^{[1
]}

Bizer, Christian ^{[1
]}

Paulheim, Heiko ^{[1
]}

机构：

[1] Univ Mannheim, Data & Web Sci Grp, B6,26, D-68159 Mannheim, Germany

来源：

JOURNAL OF WEB SEMANTICS | 2015年 / 35卷

关键词：

Linked Open Data; Data mining; RapidMiner;

D O I：

10.1016/j.websem.2015.06.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Lots of data from different domains are published as Linked Open Data (LOD). While there are quite a few browsers for such data, as well as intelligent tools for particular purposes, a versatile tool for deriving additional knowledge by mining the Web of Linked Data is still missing. In this system paper, we introduce the RapidMiner Linked Open Data extension. The extension hooks into the powerful data mining and analysis platform RapidMiner, and offers operators for accessing Linked Open Data in RapidMiner, allowing for using it in sophisticated data analysis workflows without the need for expert knowledge in SPARQL or RDF. The extension allows for autonomously exploring the Web of Data by following links, thereby discovering relevant datasets on the fly, as well as for integrating overlapping data found in different datasets. As an example, we show how statistical data from the World Bank on scientific publications, published as an RDF data cube, can be automatically linked to further datasets and analyzed using additional background knowledge from ten different LOD datasets. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：142 / 151

页数：10

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