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Constructing Complete FP-Tree for Incremental Mining of Frequent Patterns in Dynamic Databases

  • Muhaimenul Adnan
  • Reda Alhajj
  • Ken Barker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4031)

Abstract

This paper proposes a novel approach that extends the FP-tree in two ways. First, the tree is maintained to include every attribute that occurs at least once in the database. This facilitates mining with different support values without constructing several FP-trees to satisfy the purpose. Second, the tree is manipulated in a unique way that reflects updates to the corresponding database by scanning only the updated portion, thereby reducing execution time in general. Test results on two datasets demonstrate the applicability, efficiency and effectiveness of the proposed approach.

Keywords

Association Rule Frequent Pattern Frequent Itemsets Cumulative Frequency Association Rule Mining 
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

  • Muhaimenul Adnan
    • 1
  • Reda Alhajj
    • 1
    • 2
  • Ken Barker
    • 1
  1. 1.Department of Computer ScienceUniversity of CalgaryCalgaryCanada
  2. 2.Department of Computer ScienceGlobal UniversityBeirutLebanon

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