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A Collection of Benchmark Datasets for Systematic Evaluations of Machine Learning on the Semantic Web

  • Petar Ristoski
  • Gerben Klaas Dirk de Vries
  • Heiko Paulheim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9982)

Abstract

In the recent years, several approaches for machine learning on the Semantic Web have been proposed. However, no extensive comparisons between those approaches have been undertaken, in particular due to a lack of publicly available, acknowledged benchmark datasets. In this paper, we present a collection of 22 benchmark datasets of different sizes. Such a collection of datasets can be used to conduct quantitative performance testing and systematic comparisons of approaches.

Keywords

Linked Open Data Machine learning Datasets Benchmarking 

Notes

Acknowledgments

The work presented in this paper has been partly funded by the German Research Foundation (DFG) under grant number PA 2373/1-1 (Mine@LOD), and the Dutch national program COMMIT.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Petar Ristoski
    • 1
  • Gerben Klaas Dirk de Vries
    • 2
  • Heiko Paulheim
    • 1
  1. 1.Research Group Data and Web ScienceUniversity of MannheimMannheimGermany
  2. 2.WizeNozeAmsterdamThe Netherlands

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