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Incremental Association Rule Mining Using Materialized Data Mining Views

  • Mikołaj Morzy
  • Tadeusz Morzy
  • Zbyszko Królikowski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3261)

Abstract

Data mining is an interactive and iterative process. Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not support iterative processing of data mining queries and do not allow to re-use the results of previous queries. Consequently, mining algorithms suffer from long processing times, which are unacceptable from the point of view of interactive data mining. On the other hand, the results of consecutive data mining queries are usually very similar. This observation leads to the idea of reusing materialized results of previous data mining queries. We present the notion of a materialized data mining view and we propose two novel algorithms which aim at efficient discovery of association rules in the presence of materialized results of previous data mining queries.

Keywords

Data Mining Association Rule Frequent Itemsets Association Rule Mining Support Count 
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 2004

Authors and Affiliations

  • Mikołaj Morzy
    • 1
  • Tadeusz Morzy
    • 1
  • Zbyszko Królikowski
    • 1
  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznańPoland

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