Volume 35 Issue 5
May  2009
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Tong Yongxin, Ma Shilong, Li Yuet al. Effective algorithm for mining compressed frequent patterns[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(5): 640-643. (in Chinese)
Citation: Tong Yongxin, Ma Shilong, Li Yuet al. Effective algorithm for mining compressed frequent patterns[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(5): 640-643. (in Chinese)

Effective algorithm for mining compressed frequent patterns

  • Received Date: 10 Aug 2008
  • Publish Date: 31 May 2009
  • Researches of frequent-pattern mining have recently focused on discovering representative patterns to compress a large of results within a reasonable tolerance bound. A novel heuristic algorithm, approximating mining based simulated annealing (AMSA), was proposed. The algorithm uses a method based simulated-annealing to improve efficiency and quality of the compression. Our experimental studies demonstrate the algorithm is efficient and high quality on a common dataset supported by frequent itemset mining implementations repository (FIMI). The mining result of AMSA is smaller than mining results of FPclose and RPglobal by performance study. Especially, if min_sup threshold is low, RPglobal fails to generate any result within reasonable time range, while AMSA generates a concise and succinct mining result.

     

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