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�������պ����ѧѧ�� 2004, Vol. 30 Issue (08) :791-796    DOI:
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�����1, ����ƽ1, ��ϲ2*
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2. ��������ѧԺ, ���� 100083
Synthesizing algorithm for mining composite-frequent item sets
Li Guohe1, Zhao Qinping1, Wang Xi2*
1. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics�� Beijing 100083, China;
2. Beijing City College�� Beijing 100083, China

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Abstract�� 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.
Keywords�� databases   trees   rules   search theory   Apriori algorithm     
Received 2003-04-02;
About author: �����(1965-),��,����������,��ʿ��, guohe li@sina.com.
�����, ����ƽ, ��ϲ.һ��Ƶ��������Ŀ���Ļ����ⷽ��[J]  �������պ����ѧѧ��, 2004,V30(08): 791-796
Li Guohe, Zhao Qinping, Wang Xi.Synthesizing algorithm for mining composite-frequent item sets[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2004,V30(08): 791-796
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