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一种频繁复合项目集的混合求解方法
引用本文:李国和,赵沁平,王喜.一种频繁复合项目集的混合求解方法[J].北京航空航天大学学报,2004,30(8):791-796.
作者姓名:李国和  赵沁平  王喜
作者单位:1. 北京航空航天大学 计算机学院, 北京 100083;
2. 北京城市学院, 北京 100083
摘    要:关联规则挖掘的关键在于频繁项目集的求解,为了能够在含有数值类型数据的交易数据库中快速求解含有多值的频繁项目集,拓展了含有多种数值的交易数据库定义.在此基础上,根据树的思想,建立含有交易项和交易数量的树,并结合Apriori算法和智能搜索,提出在各个较小的树枝路径中求解频繁项目集求解方法FABCTA(Fast Algorithm ByCandidate Transaction Tree and Apriori).通过采用真实数据实验对比,FABCTA效率明显优于Apriori算法.

关 键 词:数据库    规则  搜索理论  Apriori算法
文章编号:1001-5965(2004)08-0791-06
收稿时间:2003-04-02
修稿时间:2003年4月2日

Synthesizing algorithm for mining composite-frequent item sets
Li Guohe,Zhao Qinping,Wang Xi.Synthesizing algorithm for mining composite-frequent item sets[J].Journal of Beijing University of Aeronautics and Astronautics,2004,30(8):791-796.
Authors:Li Guohe  Zhao Qinping  Wang Xi
Institution:1. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
2. Beijing City College, Beijing 100083, China
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
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