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基于维间扩展和事务压缩的关联规则算法改进
引用本文:张云洋,刘芳.基于维间扩展和事务压缩的关联规则算法改进[J].计算机时代,2012(9):24-26,30.
作者姓名:张云洋  刘芳
作者单位:1. 西藏大学图书馆,西藏拉萨,850012
2. 西藏大学工学院计算机系
基金项目:西藏大学青年科研培育基金项目“基于数据挖掘的藏文网页搜索算法研究”(ZDPJZK201202)
摘    要:Apriori是关联规则挖掘的经典算法,在利用该算法进行医疗数据挖掘的过程中,发现其频繁项集产生过程有一些不必要的开销,为此提出了改进算法Mypriori,利用维间扩展和事务压缩策略来提高频集发现的效率,并通过实验验证了算法的有效性.

关 键 词:关联规则  维间扩展  事务压缩  Apriori  Mypriori

Improvement of associative rule algorithm based on dimensional expansion and transaction reduction
Zhang Yunyang , Liu Fang.Improvement of associative rule algorithm based on dimensional expansion and transaction reduction[J].Computer Era,2012(9):24-26,30.
Authors:Zhang Yunyang  Liu Fang
Affiliation:1.The library of Tibet University,Lasa,Xizhang 850012,China;2.computer engineering dept,engineering institute of Tibet University)
Abstract:Apriori algorithm is a classic algorithm for associative rules.When applying to medical data mining,Apriori will generate some unnecessary operations in the process of finding frequent item sets.An improved algorithm named Mypriori is presented.Mypriori uses two tactics to enhance frequent item sets producing,which are called dimensional expansion and transaction reduction.Mypriori is proved to be effective through data mining experiments.
Keywords:association rules  expansion between dimensions  transaction reduction  Apriori  Mypriori
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