基于矩阵和权重下的并行改进算法  

Parallel Improved Algorithm Based on Matrix and Weight

作　　者：周迎 王芳 黄树成 ZHOU Ying;WANG Fang;HUANG Shucheng(College of Computer Science,Jiangsu University of Science and Technology,Zhenjiang 212001)

机构地区：[1]江苏科技大学计算机学院,镇江212001

出　　处：《计算机与数字工程》2022年第10期2259-2262,2269,共5页Computer & Digital Engineering

基　　金：国家自然科学基金项目“基于鲁棒表现建模的目标跟踪方法研究”(编号:61772244)资助。

摘　　要：经典的Apriori算法能够有效的发现数据之间隐藏的内在关系,但该算法也存在着候选集数量越大开销越大的问题。针对这个问题,文中提出一种新的改进算法RTI_Apriori。其思想是:引入矩阵来存储事务信息,分别用0和1来表示项集出现的情况,经由矩阵操作,计算项集的支持度,再依照着结果扫描删减掉不满足条件的项集,最终生成相应的关联规则。实验表明:改进后的算法不必再对数据库的多次扫描,比原有算法的效率更高。The classic Apriori algorithm can effectively discover the hidden internal relationship between data. However,this algorithm also has many shortcomings that the larger the number of candidate sets,the greater the cost. To solve this problem,a new improved algorithm RTI_Apriori is proposed. The idea is that a matrix is introduced to store transaction information,and 0 and 1 are used to represent the occurrence of item sets respectively. The operation of the matrix is used to calculate the support degree of item sets,and then the item sets that do not meet the conditions are deleted according to the results,and the corresponding association rules are finally generated. Experiments show that the improved algorithm avoids multiple scanning of database and is more efficient than the original algorithm.

关 键 词：APRIORI 关联规则 频繁项集 RTI_Apriori 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]