Mining the Web of Linked Data with RapidMiner

Petar Ristoski, Christian Bizer, Heiko Paulheim


Lots of data from dierent domains is 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 theWeb 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 oers 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 dierent 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 dierent LOD datasets.

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Type of Paper: Research Paper
Keywords: Linked Open Data, Data Mining, RapidMiner
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