[1]李雷,黄蓉.基于Apriori的快速剪枝和连接的新算法[J].计算机技术与发展,2014,24(05):31-35.
　LI Lei,HUANG Rong.A New Quick Pruning and Connection Algorithm Based on Apriori[J].,2014,24(05):31-35.
点击复制

基于Apriori的快速剪枝和连接的新算法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年05期
页码:
31-35
栏目:
智能、算法、系统工程
出版日期:
2014-05-31

文章信息/Info

Title:
A New Quick Pruning and Connection Algorithm Based on Apriori
文章编号:
1673-629X（2014）05-0031-05
作者:
李雷; 黄蓉
南京邮电大学 自动化学院
Author(s):
LI Lei; HUANG Rong
关键词:
关联规则; Apriori; QPCA; 数据挖掘
Keywords:
association rules; Apriori; QPCA; data mining
分类号:
TP301.6
文献标志码:
A
摘要:
挖掘关联规则是目前数据挖掘领域热点研究话题之一。它的目的在于在数据库中挖掘有趣的关联规则。在关联规则分析及Apriori算法分析上，针对Apriori算法的瓶颈问题，许多有效的改进算法被提出。文中提出了QPCA算法。该算法利用矩阵分析的方法，仅需要扫描数据库一次，同时此算法优化了连接和剪枝操作，通过快速的剪枝和连接可以很快地获取最少的候选项集，避免了频繁项集之间的重复判断连接，因此大大提高了算法的效率。实验结果表明，该算法在挖掘时间上有很大提高。
Abstract:
Mining of association rules is an important research topic in data mining field. Its purpose is to mine interesting associations in transaction database. For the analysis of association rules and Apriori algorithm principle,in view of the bottlenecks of Apriori algorithm, lots of improved algorithms are proposed. In this paper,put forward the QPCA. The algorithm uses the method of matrix analysis,only needs to scan the database once. At the same time,the algorithm optimizes the pruning and connection operation,which can quickly obtain less candidate itemsets by quick pruning and connection,avoiding duplication of judgment and connection between frequent itemsets. Thus it's greatly improving the efficiency of the algorithm. The experimental results show that the algorithm has great improvement in mining speed.

相似文献/References:

[1]李雷 丁亚丽 罗红旗.基于规则约束制导的入侵检测研究[J].计算机技术与发展,2010,(03):143.
　LI Lei,DING Ya-li,LUO Hong-qi.Intrusion Detection Technology Research Based on Homing - Constraint Rule[J].,2010,(05):143.
[2]王爱平 王占凤 陶嗣干 燕飞飞.数据挖掘中常用关联规则挖掘算法[J].计算机技术与发展,2010,(04):105.
　WANG Ai-ping,WANG Zhan-feng,TAO Si-gan,et al.Common Algorithms of Association Rules Mining in Data Mining[J].,2010,(05):105.
[3]张广路 雷景生 吴兴惠.一种改进的Apriori关联规则挖掘算法（英文）[J].计算机技术与发展,2010,(06):84.
　ZHANG Guang-lu,LEI Jing-sheng,WU Xing-hui.An Improved Apriori Algorithm for Mining Association Rules[J].,2010,(05):84.
[4]耿波 仲红 徐杰 闫娜娜.用关联分析法对负荷预测结果进行二次处理[J].计算机技术与发展,2008,(04):171.
　GENG Bo,ZHONG Hong,XU Jie,et al.Using Correlation Analysis to Treat Load Forecasting Results[J].,2008,(05):171.
[5]文拯 梁建武 陈英.关联规则算法的研究[J].计算机技术与发展,2009,(05):56.
　WEN Zheng,LIANG Jian-wu,CHEN Ying.Research of Association Rules Algorithm[J].,2009,(05):56.
[6]王晓宇 秦锋 程泽凯 邹洪侠.关联规则挖掘技术的研究与应用[J].计算机技术与发展,2009,(05):220.
　WANG Xiao-yu,QIN Feng,CHENG Ze-kai,et al.Investigation and Application of Association Rules Mining[J].,2009,(05):220.
[7]陈伟.Apriori算法的优化方法[J].计算机技术与发展,2009,(06):80.
　CHEN Wei.Method of Apriori Algorithm Optimization[J].,2009,(05):80.
[8]吕刚[] 郑诚.基于本体的关联规则在电子商务中的应用[J].计算机技术与发展,2009,(06):250.
　LU Gang,ZHENG Cheng.Association Rules with Ontological Information in E- Commerce[J].,2009,(05):250.
[9]郑春香 韩承双.关联规则研究及在远程教育考试系统中的应用[J].计算机技术与发展,2009,(08):186.
　ZHENG Chun-xiang,HAN Cheng-shuang.Research on Association Rule Mining and Application of Long- Distance Education System[J].,2009,(05):186.
[10]郑春香 韩承双 董甲东.关联规则技术在教学评价中的应用[J].计算机技术与发展,2009,(09):215.
　ZHENG Chun-xiang,HAN Cheng-shuang,DONG Jia-dong.Application of Association Rule Mining in Teaching Appraisal[J].,2009,(05):215.
[11]朱其祥 徐勇 张林.基于改进Apriori算法的关联规则挖掘研究[J].计算机技术与发展,2006,(07):102.
　ZHU Qi-xiang,XU Yong,ZHANG Lin.Research on Mining Association Rule Based on Improved Apriori Algorithm[J].,2006,(05):102.
[12]刘木林,朱庆华. 基于Hadoop的关联规则挖掘算法研究--以Apriori算法为例[J].计算机技术与发展,2016,26(07):1.
　LIU Mu-lin,ZHU Qing-hua. Research on Association Rules Mining Algorithm Based on Hadoop-Taking Apriori as an Example[J].,2016,26(05):1.
[13]秦军[],郝天曙[],董倩倩[]. 基于MapReduce的Apriori算法并行化改进[J].计算机技术与发展,2017,27(04):64.
　QIN Jun[],HAO Tian-shu[],DONG Qian-qian[]. Parallel Improvement of Apriori Algorithm Based on MapReduce[J].,2017,27(05):64.
[14]李德辰,吕一帆,赵学健.一种基于预判筛选的频繁项集挖掘算法[J].计算机技术与发展,2018,28(05):99.[doi:10.3969/ j. issn.1673-629X.2018.05.023]
　LI De-chen,LYU Yi-fan,ZHAO Xue-jian.A Frequent Item-set Mining Algorithm Based on Prejudgment and Screening[J].,2018,28(05):99.[doi:10.3969/ j. issn.1673-629X.2018.05.023]
[15]许德心,李玲娟.基于 Spark 的关联规则挖掘算法并行化研究[J].计算机技术与发展,2019,29(03):30.[doi:10.3969/ j. issn.1673-629X.2019.03.006]
　XU De-xin,LI Ling-juan.Research on Parallelization of Association Rules Mining Algorithm Based on Spark[J].,2019,29(05):30.[doi:10.3969/ j. issn.1673-629X.2019.03.006]

更新日期/Last Update: 1900-01-01