Semantic Analytical Reports: A Framework for Post-processing Data Mining Results

  • Tomáš Kliegr
  • Martin Ralbovský
  • Vojtěch Svátek
  • Milan Šimůnek
  • Vojtěch Jirkovský
  • Jan Nemrava
  • Jan Zemánek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5722)

Abstract

Intelligent post-processing of data mining results can provide valuable knowledge. In this paper we present the first systematic solution to post-processing that is based on semantic web technologies. The framework input is constituted by PMML and description of background knowledge. Using the Topic Maps formalism, a generic Data Mining ontology and Association Rule Mining ontology were designed. Through combination of a content management system and a semantic knowledge base, the analyst can enter new pieces of information or interlink existing ones. The information is accessible either via semi-automatically authored textual analytical reports or via semantic querying. A prototype implementation of the framework for generalized association rules is demonstrated on the PKDD’99 Financial Data Set.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Tomáš Kliegr
    • 1
  • Martin Ralbovský
    • 1
  • Vojtěch Svátek
    • 1
  • Milan Šimůnek
    • 1
  • Vojtěch Jirkovský
    • 2
  • Jan Nemrava
    • 1
  • Jan Zemánek
    • 1
  1. 1.Faculty of Informatics and StatisticsUniversity of Economics, PraguePraha 3Czech Republic
  2. 2.Dept. of Computer Science and EngineeringCzech Technical UniversityPraha 2Czech Republic

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