ORE - A Tool for Repairing and Enriching Knowledge Bases

  • Jens Lehmann
  • Lorenz Bühmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6497)

Abstract

While the number and size of Semantic Web knowledge bases increases, their maintenance and quality assurance are still difficult. In this article, we present ORE, a tool for repairing and enriching OWL ontologies. State-of-the-art methods in ontology debugging and supervised machine learning form the basis of ORE and are adapted or extended so as to work well in practice. ORE supports the detection of a variety of ontology modelling problems and guides the user through the process of resolving them. Furthermore, the tool allows to extend an ontology through (semi-)automatic supervised learning. A wizard-like process helps the user to resolve potential issues after axioms are added.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jens Lehmann
    • 1
  • Lorenz Bühmann
    • 1
  1. 1.AKSW research groupUniversity of LeipzigGermany

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