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基于事务拆分的超团挖掘算法
引用本文:卓鹏,肖波,蔺志青.基于事务拆分的超团挖掘算法[J].计算机工程,2009,35(20):62-65.
作者姓名:卓鹏  肖波  蔺志青
作者单位:北京邮电大学电信工程学院,北京,100876
基金项目:国家 "863"计划基金资助项目,高等学校学科创新引智计划基金资助项目 
摘    要:为发现处在低支持度下的潜在有趣模式,针对传统基于支持度策略的模式发现算法存在的问题,提出一种基于改进Relim算法的超团模式挖掘算法,将一个事务拆分为2个或多个事务,把相同事务进行压缩,并用Relim算法的思想进行超团模式挖掘。仿真实验结果表明,该算法能有效提高超团模式的挖掘效率。

关 键 词:数据挖掘  关联规则  超团模式  事务拆分  Relim算法
修稿时间: 

Hyperclique Mining Algorithm Based on Transaction Splitting
ZHUO Peng,XIAO Bo,LIN Zhi-qing.Hyperclique Mining Algorithm Based on Transaction Splitting[J].Computer Engineering,2009,35(20):62-65.
Authors:ZHUO Peng  XIAO Bo  LIN Zhi-qing
Affiliation:(School of Telecommunication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876)
Abstract:In order to discover potential interesting patterns at low levels of support, aiming at problems in traditional support degree-based mode discovering algorithm, this paper proposes a hyperclique mining algorithm based on improved Relim algorithm. It splits a transaction into two or more transactions and compresses the same transactions. By using the idea of Relim algorithm, the hyperclique pattern is mined. Simulation experimental results show this algorithm can promote the mining efficiency for hyperclique pattern.
Keywords:data mining  association rules  hyperclique pattern  transaction splitting  Relim algorithm
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