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Mining the Web of Linked Data with Rapidminer

14 Pages Posted: 18 Jul 2018 First Look: Accepted

See all articles by Petar Ristoski

Petar Ristoski

University of Mannheim - Data and Web Science Group

Christian Bizer

University of Mannheim - Data and Web Science Group

Heiko Paulheim

University of Mannheim - Data and Web Science Group

Multiple version iconThere are 2 versions of this paper

Abstract

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, 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.

Keywords: Linked Open Data, Data mining, RapidMiner

Suggested Citation

Ristoski, Petar and Bizer, Christian and Paulheim, Heiko, Mining the Web of Linked Data with Rapidminer (2015). Journal of Web Semantics First Look . Available at SSRN: https://ssrn.com/abstract=3199209 or http://dx.doi.org/10.2139/ssrn.3199209

Petar Ristoski (Contact Author)

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

Christian Bizer

University of Mannheim - Data and Web Science Group

L 5, 2 - 2. OG
68161 Mannheim
Germany

Heiko Paulheim

University of Mannheim - Data and Web Science Group ( email )

L 5, 2 - 2. OG
68161 Mannheim
Germany

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