Ontology-Enhanced Association Mining

  • Vojtěch Svátek
  • Jan Rauch
  • Martin Ralbovský
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4289)


The roles of ontologies in KDD are potentially manifold. We track them through different phases of the KDD process, from data understanding through task setting to mining result interpretation and sharing over the semantic web. The underlying KDD paradigm is association mining tailored to our 4ft-Miner tool. Experience from two different application domains—medicine and sociology—is presented throughout the paper. Envisaged software support for prior knowledge exploitation via customisation of an existing user-oriented KDD tool is also discussed.


Association Rule Semantic Relation Domain Ontology Semantic Type Qualitative Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Vojtěch Svátek
    • 1
  • Jan Rauch
    • 1
  • Martin Ralbovský
    • 2
  1. 1.Department of Information and Knowledge EngineeringUniversity of Economics, PraguePraha 3Czech Republic
  2. 2.Faculty of Mathematics and PhysicsCharles University in PraguePraha 2Czech Republic

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