关联规则中Apriori算法的研究与改进
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摘要
随着科学技术的发展,人们可以更快、更方便地获取数据、保存数据,数据的量和复杂程度都是前所未见。该文对数据挖掘技术中的关联规则挖掘进行了系统的分析和研究,并在经典的Apriori算法的基础上改进了一个算法。该算法是一种基于矩阵的关联规则挖掘算法,通过扫描将数据库映射为0-1矩阵,直接在矩阵上进行运算,避免了反复扫描的过程,还对Apriori性质进行了引申和利用,对矩阵进行彻底的压缩。理论分析和实验证明了改进算法在效率上的提高。
With the rapid development of information technologies,people can get data and store data quickly and conveniently,which results in the unprecedented rising of the quantity and complexity of the data.This thesis presents the systematic analysis and research on the data mining and association rule mining.The algorithm is an algorithm of mining association rules based on matrix.The new algorithm maps the database into a 0-1matrix,computing directly on the matrix and avoiding scanning the database repeatedly.And also extended and utilization the properties of the Apriori,the matrix will be compressed more thoroughly.At the end of the paper,a theoretical analysis and experiment will been given.
With the rapid development of information technologies,people can get data and store data quickly and conveniently,which results in the unprecedented rising of the quantity and complexity of the data.This thesis presents the systematic analysis and research on the data mining and association rule mining.The algorithm is an algorithm of mining association rules based on matrix.The new algorithm maps the database into a 0-1matrix,computing directly on the matrix and avoiding scanning the database repeatedly.And also extended and utilization the properties of the Apriori,the matrix will be compressed more thoroughly.At the end of the paper,a theoretical analysis and experiment will been given.
引文
[1]陆楠.关联规则的挖掘及其算法的研究[D].长春:吉林大学,2007.
[2]伊卫国.基于关联规则与决策树的预测方法研究及其应用[D].大连:大连海事大学,2012.
[3]Fayyad U M,Piatetsky-Shapiro G,Smyth P,et al.Advances in knowledge discovery and data mining[J].1996.
[4]Agrawal R,Srikant R.Fast algorithms for mining association rules[C].Proc.20th int.conf.very large data bases,VLDB,1994,1215:487-499.
[5]魏茂林.Apriori算法的改进及其在教育决策系统中的应用[D].长春:吉林大学,2010.
[6]Agrawal R,Srikant R.Fast algorithms for mining association rules[C].Proc.20th int.conf.very large data bases,VLDB,1994,1215:487-499.
[7]李超,余昭平.基于矩阵的Apriori算法改进[J].计算机工程,2006,32(23):68-69.
[8]曾万聃,周绪波,戴勃,等.关联规则挖掘的矩阵算法[J].计算机工程,2006,32(2):45-47.
[2]伊卫国.基于关联规则与决策树的预测方法研究及其应用[D].大连:大连海事大学,2012.
[3]Fayyad U M,Piatetsky-Shapiro G,Smyth P,et al.Advances in knowledge discovery and data mining[J].1996.
[4]Agrawal R,Srikant R.Fast algorithms for mining association rules[C].Proc.20th int.conf.very large data bases,VLDB,1994,1215:487-499.
[5]魏茂林.Apriori算法的改进及其在教育决策系统中的应用[D].长春:吉林大学,2010.
[6]Agrawal R,Srikant R.Fast algorithms for mining association rules[C].Proc.20th int.conf.very large data bases,VLDB,1994,1215:487-499.
[7]李超,余昭平.基于矩阵的Apriori算法改进[J].计算机工程,2006,32(23):68-69.
[8]曾万聃,周绪波,戴勃,等.关联规则挖掘的矩阵算法[J].计算机工程,2006,32(2):45-47.