基于加权关联规则的数据共享效果跟踪方法设计  

Design of Data Sharing Effect Tracking Method Based on Weighted Association Rules

作　　者：刘亚男[1] LIU Ya-nan(Anhui Business and Technology College,Hefei,Anhui 231131,China)

机构地区：[1]安徽工商职业学院,安徽合肥231131

出　　处：《河北北方学院学报（自然科学版）》2022年第3期43-47,共5页Journal of Hebei North University:Natural Science Edition

基　　金：2018年安徽省高校优秀青年人才基金支持计划一般项目“基于区块链技术的去中心化电子商务信用系统模型构建及优化策略研究——以安徽省为例”(gxyq2018251);2018安徽省高校人文社会科学研究一般项目“基于BP神经网络的C2C电子商务网站信任评价模型研究(SK2018B005)”;安徽省职业与成人教育协会课题产教融合背景下高职电子商务专业创新创业教学模式研究(AGZ18109)。

摘　　要：目的为了更好地设计数据共享方案,需要对历史数据进行数据共享效果跟踪,以获取数据共享间的内在关联,针对当前数据共享跟踪中存在的运行时间长、结果准确度较低等问题,提出基于加权关联规则的数据共享效果跟踪方法。方法构建数据共享的模糊关联规则,计算模糊关联支持度与置信度,据此对数据分类进行调整,并映射到多维子空间内。融合数据关联映射结果,获得不同维度内数据共享效果与同一维度内数据共享效果的差异化算法,实现数据共享效果的准确跟踪。结果实验结果表明,数据维度越大,算法运行时间越长,且时间增长幅度也随之增大。当数据量为800个时,所提算法所需时间为20.07 s,准确度为95.4%。当数据量为2000个时,所提算法所需时间为45.71 s,准确度为95.1%。结论所提方法的运行时间相对较短,跟踪结果的准确度较现有方法有一定提高,具有一定的应用价值。Objective To better design the data sharing scheme,it is necessary to track the data sharing effect of historical data,so as to obtain the internal relationship between data sharing.Aimed at the problems of long running time and low accuracy of results in current data sharing tracking,a data sharing effect tracking method based on weighted association rules was proposed.Methods The fuzzy association rules of data sharing were constructed,and the support and confidence of fuzzy association were calculated.Then,the data classification was adjusted and mapped into multidimensional subspace.By fusing the data association mapping results,the differential algorithm of data sharing effect in different dimensions and data sharing effect in the same dimension was obtained,and the accurate tracking of data sharing effect was realized.Results The experimental results showed that the larger the data dimension was,the longer the running time of the algorithm would be,and the time growth would also increase.When the amount of data was 800,the time required by the proposed algorithm was 20.07 s and the accuracy was 95.4%.When the amount of data was 2000,the time required by the proposed algorithm was 45.71 s and the accuracy was 95.1%.Conclusion The running time of the proposed method is relatively short,and the accuracy of tracking results is improved compared with the existing methods,which has certain application value.

关 键 词：加权关联规则 数据共享 效果跟踪 数据挖掘 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]