Scalable, Distributed and Dynamic Mining of Association Rules

  • V.S. Ananthanarayana
  • D.K. Subramanian
  • M.N Murty
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1970)


We propose a novel pattern tree called Pattern Count tree (PC-tree) which is a complete and compact representation of the database. We show that construction of this tree and then generation of all large itemsets requires a single database scan where as the current algorithms need at least two database scans. The completeness property of the PC-tree with respect to the database makes it amenable for mining association rules in the context of changing data and knowledge, which we call dynamic mining. Algorithms based on PC-tree are scalable because PC-tree is compact. We propose a partitioned distributed architecture and an efficient distributed association rule mining algorithm based on the PC-tree structure.


Association Rule Frequent Itemsets Association Rule Mining Compact Representation Transaction Database 
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 2000

Authors and Affiliations

  • V.S. Ananthanarayana
    • 1
  • D.K. Subramanian
    • 1
  • M.N Murty
    • 1
  1. 1.Dept. of Computer Science and AutomationIndian Institute of ScienceBangaloreIndia

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