Mining Local Association Rules from Temporal Data Set

  • Fokrul Alom Mazarbhuiya
  • Muhammad Abulaish
  • Anjana Kakoti Mahanta
  • Tanvir Ahmad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)


In this paper, we present a novel approach for finding association rules from locally frequent itemsets using rough set and boolean reasoning. The rules mined so are termed as local association rules. The efficacy of the proposed approach is established through experiment over retail dataset that contains retail market basket data from an anonymous Belgian retail store.


Data mining Temporal data mining Local association rule mining Rough set Boolean reasoning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Fokrul Alom Mazarbhuiya
    • 1
  • Muhammad Abulaish
    • 2
  • Anjana Kakoti Mahanta
    • 3
  • Tanvir Ahmad
    • 4
  1. 1.College of Computer ScienceKing Khalid UniversityAbha
  2. 2.Department of Computer ScienceJamia Millia IslamiaDelhiIndia
  3. 3.Department of Computer ScienceGauhati UniversityIndia
  4. 4.Department of Computer EngineeringJamia Millia IslamiaDelhiIndia

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