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Online Mining of Weighted Fuzzy Association Rules

  • Mehmet Kaya
  • Reda Alhajj
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2869)

Abstract

Mining useful information and helpful knowledge from data transactions is evolving as an important research area. Current online techniques for mining association rules identify the relationship among transactions using binary values. However, transactions with quantitative values are commonly encountered in real-life applications. In this paper, we address this problem by introducing a fuzzy adjacency lattice, and then integrate the lattice structure with linguistic weights in a way to reflect the importance of items. Experiments conducted using synthetic data show the effectiveness of the proposed method for online generation of weighted fuzzy association rules.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Mehmet Kaya
    • 1
  • Reda Alhajj
    • 2
  1. 1.Department of Computer EngineeringFirat UniversityElazigTURKEY
  2. 2.Department of Computer ScienceUniversity of CalgaryCalgaryCANADA

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