An efficient algorithm of mining association rules based on digital pure subset

  • Authors:

  • Yu-Lu Liu;Gang Fang;Jiang Xiong;Yuan-Bin Wu

  • Affiliations:

  • College of Math and Computer Science, Chongqing Three Gorges University, Chongqing, P.R. China;College of Math and Computer Science, Chongqing Three Gorges University, Chongqing, P.R. China;College of Math and Computer Science, Chongqing Three Gorges University, Chongqing, P.R. China;College of Math and Computer Science, Chongqing Three Gorges University, Chongqing, P.R. China

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
  • Year:
  • 2009

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Abstract

This paper proposes an efficient algorithm of double search mining association rules based on digital pure subset, which uses the method of forming digital pure subset of transaction to generate candidate itemsets, and uses digital character to reduce the number of scanned transactions when computing support of itemsets after these transactions are turned into digital transaction by binary. In addition, the algorithm uses logical operation to compute support of candidate itemsets, and uses the way of ascending value to form pure subset of digital transaction via maximal and minimal transactions synchronously close to intermediate value, which is different from traditional algorithms of double search mining association rules. The experiment indicates that the efficiency of the algorithm is faster and more efficient than presented algorithms of double search mining association rules.