Volume 30 Issue 08
Aug.  2004
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Li Guohe, Zhao Qinping, Wang Xiet al. Synthesizing algorithm for mining composite-frequent item sets[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(08): 791-796. (in Chinese)
Citation: Li Guohe, Zhao Qinping, Wang Xiet al. Synthesizing algorithm for mining composite-frequent item sets[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(08): 791-796. (in Chinese)

Synthesizing algorithm for mining composite-frequent item sets

  • Received Date: 02 Apr 2003
  • Publish Date: 31 Aug 2004
  • It is very important to get the frequent item set in the associate rule mining. In order to fast obtain the frequent item set from a database that includes multiple values, the definition of transaction database was extended. And then by the tree concept, a special tree was built in which every node is formed by item and item’s count. At last, on the foundation of Apriori Algorithm and Artificial Intelligent Search, FABCTA(fast algorithm by candidate transaction tree and apriori) was presented to solve the frequent item set in small branches of tree. By the test on real data, FABCTA is more efficient than Apriori algorithm.

     

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