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Mining Indirect Least Association Rule

  • Zailani Abdullah
  • Tutut Herawan
  • Mustafa Mat Deris
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 285)

Abstract

Indirect pattern can be considered as one of the interesting information that is hiding in transactional database. It corresponds to the property of high dependencies between two items that are rarely appeared together but indirectly occurred through another items. Therefore, we propose an algorithm for Mining Indirect Least Association Rule (MILAR) from the real dataset. MILAR is embedded with a scalable least measure called Critical Relative Support (CRS). The experimental results indicate that MILAR is capable in generating the indirect least association rules from the given dataset.

Keywords

Mining Indirect Least Association rule 

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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  • Zailani Abdullah
    • 1
  • Tutut Herawan
    • 2
    • 3
  • Mustafa Mat Deris
    • 4
  1. 1.Department of Computer ScienceUniversiti Malaysia TerengganuKuala TerengganuMalaysia
  2. 2.Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia
  3. 3.Universitas Teknologi YogyakartaYogyakartaIndonesia
  4. 4.Faculty of Science Computer and Information TechnologyUniversiti Tun Hussein Onn MalaysiaBatu PahatMalaysia

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