Interesting Patterns Extraction Using Prior Knowledge

  • Laurent Brisson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4265)


One important challenge in data mining is to extract interesting knowledge and useful information for expert users. Since data mining algorithms extracts a huge quantity of patterns it is therefore necessary to filter out those patterns using various measures. This paper presents IMAK, a part-way interestingness measure between objective and subjective measure, which evaluates patterns considering expert knowledge. Our main contribution is to improve interesting patterns extraction using relationships defined into an ontology.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Laurent Brisson
    • 1
  1. 1.Laboratoire I3SUniversité de NiceFrance

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