mBAR: A Materialized Bitmap Based Association Rule Algorithm

  • Authors:
  • Woon-Hak Kang;Dong-Hyun Kim;Sang-Won Lee

  • Affiliations:
  • Sungkyunkwan University;Sungkyunkwan University;Sungkyunkwan University

  • Venue:
  • ICDEW '05 Proceedings of the 21st International Conference on Data Engineering Workshops
  • Year:
  • 2005

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Abstract

With the rapid progress in information technology, the data mining technique has been exploited in various applications. The association rule(hereafter, AR) mining, one of the most popular data mining techniques, is to find the frequent itemsets which occur commonly in transaction database. Of the various AR algorithms, the Apriori is most popular, and it has been continuously improved during the past decade. Even with recent version, however, it is very time consuming for the Apriori-based algorithms to count frequent itemset since, basically for each k-size item set, we need to compute its support on-the-fly.