[1]王妍 王丽君 方芸.基于关联规则的搭配进货系统的研究与实现[J].计算机技术与发展,2012,(01):137-139.
　WANG Yan,WANG Li-jun,FANG Yun.Research and Realization of Restocking System Based on Association Rules[J].,2012,(01):137-139.
点击复制

基于关联规则的搭配进货系统的研究与实现()
分享到：

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

卷:
期数:
2012年01期
页码:
137-139
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Research and Realization of Restocking System Based on Association Rules
文章编号:
1673-629X（2012）01-0137-03
作者:
王妍 王丽君 方芸
曲阜师范大学计算机科学学院
Author(s):
WANG Yan;  WANG Li-jun;  FANG Yun
Computer Science Institute, Qufu Normal University
关键词:
关联规则; 数据挖掘; 搭配进货
Keywords:
association rules ;  data mining ; restocking system
分类号:
TP31
文献标志码:
A
摘要:
为了解决商品进货无关联的现状，找到商品间的关联规则，更好地进行商品的搭配进货，从而提高进货效率，文中引入了关联规则的思想，并利用规则进行了商品关联规则的挖掘。在分析了关联规则挖掘的算法后，将其应用到超市商品数据库中，利用关联规则挖掘出大量数据中项集即商品之间的相互关联，并抽取出有价值的商品关联规则，利用支持度和平衡度这两个度量概念，优化出强规则集，并用这一思想成功设计了PLM即产品全生命周期管理中的搭配进货系统
Abstract:
In order to address the status of commodity stock that are not associated, find associations rules of commodities and matching of goods stock, so as to improve the efficiency of stock,introduced the idea of association rules and used rules for commodity association rule mining. In this paper, algorithm of association rules mining is analyzed and applied to the database of supermarket goods. The valuable association rules of supermarket goods were extracted, then the strong rules were extracted by using the two metrics concept of support and balance. Finally ,all strong rules were applied to the restocked system of PLM

相似文献/References:

[1]项响琴 汪彩梅.基于聚类高维空间算法的离群数据挖掘技术研究[J].计算机技术与发展,2010,(01):120.
　XIANG Xiang-qin,WANG Cai-mei.Study of Outlier Data Mining Based on CLIQUE Algorithm[J].,2010,(01):120.
[2]吉同路 柏永飞 王立松.住宅与房地产电子政务中数据挖掘的应用研究[J].计算机技术与发展,2010,(01):235.
　JI Tong-lu,BAI Yong-fei,WANG Li-song.Study and Application of Data Mining in E-government of House and Real Estate Industry[J].,2010,(01):235.
[3]杨静 张楠男 李建 刘延明 梁美红.决策树算法的研究与应用[J].计算机技术与发展,2010,(02):114.
　YANG Jing,ZHANG Nan-nan,LI Jian,et al.Research and Application of Decision Tree Algorithm[J].,2010,(01):114.
[4]赵裕啸 倪志伟 王园园 伍章俊.SQL Server 2005数据挖掘技术在证券客户忠诚度的应用[J].计算机技术与发展,2010,(02):229.
　ZHAO Yu-xiao,NI Zhi-wei,WANG Yuan-yuan,et al.Application of Data Mining Technology of SQL Server 2005 in Customer Loyalty Model in Securities Industry[J].,2010,(01):229.
[5]张笑达 徐立臻.一种改进的基于矩阵的频繁项集挖掘算法[J].计算机技术与发展,2010,(04):93.
　ZHANG Xiao-da,XU Li-zhen.An Advanced Frequent Itemsets Mining Algorithm Based on Matrix[J].,2010,(01):93.
[6]吴楠 胡学钢.基于聚类分区的序列模式挖掘算法研究[J].计算机技术与发展,2010,(06):109.
　WU Nan,HU Xue-gang.Research on Clustering Partition-Based Approach of Sequential Pattern Mining[J].,2010,(01):109.
[7]吴青 傅秀芬.水平分布数据库的正负关联规则挖掘[J].计算机技术与发展,2010,(06):113.
　WU Qing,FU Xiu-fen.Positive and Negative Association Rules Mining on Horizontally Partitioned Database[J].,2010,(01):113.
[8]孙名松 邸明星 王湛昱.多决策树算法在P2P网络流量检测中的应用[J].计算机技术与发展,2010,(06):126.
　SUN Ming-song,DI Ming-xing,WANG Zhan-yu.Application of Decision Tree Algorithm in Traffic Detection of P2P Network[J].,2010,(01):126.
[9]孟魁杰 董莹 赵宗涛.一种基于数据挖掘的无人飞行器故障分析方法[J].计算机技术与发展,2010,(06):225.
　MENG Kui-jie,DONG Ying,ZHAO Zong-tao.A Fault Analysis Method Based on Data Mining for Unmanned Aerial Vehicle[J].,2010,(01):225.
[10]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,(01):80.
[11]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,(01):143.
[12]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,(01):105.
[13]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,(01):84.
[14]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,(01):56.
[15]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,(01):220.
[16]王敏 刘希玉.Apriori算法在税务系统中的应用[J].计算机技术与发展,2009,(11):175.
　WANG Min,LIU Xi-yu.Application of Apriori Algorithm in Tax System[J].,2009,(01):175.
[17]董彩云 刘培华.数据挖掘技术在远程教育教学中的应用[J].计算机技术与发展,2009,(02):179.
　DONG Cai-yun,LIU Pei-hua.Application of Data Mining Technology in Instance Education[J].,2009,(01):179.
[18]刘军锋 李景文 陈大克 邓晓斌.一种改进的关联规则自顶向下算法[J].计算机技术与发展,2008,(02):136.
　LIU Jun-feng,LI Jing-wen,CHEN Da-ke,et al.An Improved Top to Bottom Algorithm for Mining Association Rules[J].,2008,(01):136.
[19]王伟 高亮 吴涛.基于遗传算法的长频繁项集挖掘方法[J].计算机技术与发展,2008,(04):19.
　WANG Wei,GAO Liang,WU Tao.A Method of Mining Long Frequent Itemset Based on Genetic Algorithm[J].,2008,(01):19.
[20]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,(01):171.

备注/Memo

备注/Memo:
山东省软科学项目（2010RKGA1053）王妍（1980-），女，山东曲阜人，实验师，硕士研究生，研究方向为人工智能、软件工程、数据挖掘
更新日期/Last Update: 1900-01-01