Automating RDF Dataset Transformation and Enrichment

  • Mohamed Ahmed Sherif
  • Axel-Cyrille Ngonga Ngomo
  • Jens Lehmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9088)

Abstract

With the adoption of RDF across several domains, come growing requirements pertaining to the completeness and quality of RDF datasets. Currently, this problem is most commonly addressed by manually devising means of enriching an input dataset. The few tools that aim at supporting this endeavour usually focus on supporting the manual definition of enrichment pipelines. In this paper, we present a supervised learning approach based on a refinement operator for enriching RDF datasets. We show how we can use exemplary descriptions of enriched resources to generate accurate enrichment pipelines. We evaluate our approach against eight manually defined enrichment pipelines and show that our approach can learn accurate pipelines even when provided with a small number of training examples.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mohamed Ahmed Sherif
    • 1
  • Axel-Cyrille Ngonga Ngomo
    • 1
  • Jens Lehmann
    • 1
  1. 1.Department of Computer ScienceUniversity of LeipzigLeipzigGermany

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