VTK: Vertical Mining of Top-Rank-K Frequent Patterns

  • Authors:
  • Guo-Dong Fang;Zhi-Hong Deng

  • Affiliations:
  • -;-

  • Venue:
  • FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02
  • Year:
  • 2008

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Abstract

Mining Top-Rank-K frequent patterns is a new topic in frequent pattern mining. In this paper, we propose a new mining algorithm called VTK, Vertical Mining of Top-Rank-k Frequent Patterns, to mining Top-Rank-K frequent patterns using some Vertical skills. Our performance study shows that the VTK method is more efficient and scalable for mining both synthetic datasets and real datasets than the algorithms proposed before.