Mining Local Association Rules from Temporal Data Set

Authors:
Fokrul Alom Mazarbhuiya;Muhammad Abulaish;Anjana Kakoti Mahanta;Tanvir Ahmad
Affiliations:
College of Computer Science, King Khalid University, Abha;Department of Computer Science, Jamia Millia Islamia, Delhi, India;Department of Computer Science, Gauhati University, India;Department of Computer Engineering, Jamia Millia Islamia, Delhi, India
Venue:
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Year:
2009

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Abstract

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.