Apriori算法改进及其在资产管理中的应用  

Improvement of Apriori Algorithm and Its Application in Asset Management

作　　者：郑斌[1] ZHENG Bin(College of Electronics and Information Science,Fujian Jiangxia University,Fuzhou 350108,China)

机构地区：[1]福建江夏学院电子信息科学学院

出　　处：《重庆科技学院学报（自然科学版）》2019年第5期54-56,76,共4页Journal of Chongqing University of Science and Technology：Natural Sciences Edition

基　　金：福建省中青年教师教育科研项目“关于轨道交通企业资产一体化管理平台的设计研究”(JAT170626)

摘　　要：在运用Apriori算法挖掘轨道交通企业资产数据时,针对Apriori算法会产生大量候选集而导致搜索速度降低等问题,构建频繁项生成优化模型,应用数据属性规约方式优化约束关联规则。实验表明,改进后的算法具有更好的时间效率,可适用于海量数据集。In this paper,the Apriori algorithm is used to dig deeper into the current rail transit asset data. A large number of candidate sets are generated for the traditional Apriori method,which leads to lower search speed. The traditional Apriori algorithm is optimized by constructing the frequent item generation optimization model and by optimizing the constraint association rules with the attribute specification method. Experiments show that the proposed algorithm has very good performance in time efficiency,especially in dealing massive data sets.

关 键 词：资产管理 数据挖掘 APRIORI算法 频繁项 属性规约 关联规则 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]