摘要
为减少多段支持度数据集成耗时,提高多段支持度数据集成效率,本文提出了一种全新的多段支持度数据集成系统。综合考虑多段支持度数据的特征,搭建了与数据集成需求契合度较高的硬件运行环境。在此基础上,基于最大频繁模式挖掘算法,设计数据流处理模块,输出挖掘的数据流频繁项集。设计多段支持度数据实时加载模块,抽取点对点同步数据,再引入5G专网数字孪生模型理念,构建多段支持度数据库,分析、集成与存储数据。根据系统测试结果可知,设计系统应用后,集成数据平均时耗最多不超过1.5 s,集成效率得到了提高。
In order to reduce the time of multi-segment support data integration and improve the efficiency of multi-segment support data integration,this paper proposes a new multi-segment support data integration system.Taking into account the characteristics of multi-segment support data,a hardware operation environment with high compatibility with data integration requirements is built.On this basis,based on the maximum frequent pattern mining algorithm,the data stream processing module is designed to output the frequent itemsets of the data stream.Design a multi-segment support data real-time loading module,extract point-to-point synchronous data,and introduce the concept of 5G private network digital twin model to build a multi-segment support database,analyze,integrate and store data.According to the system test results,after the design and application of the system,the average time consumption of integrated data is not more than 1.5 s,and the integration efficiency has been improved.
作者
何昀
陈伟
张继夫
张川
HE Yun;CHEN Wei;ZHANG Jifu;ZHANG Chuan(Aviation University of Air Force,Changchun Jilin 130021,China)
出处
《信息与电脑》
2023年第3期129-131,共3页
Information & Computer
关键词
最大频繁模式挖掘
多段支持度
数据集成
5G专网数字孪生模型
maximum frequent pattern mining
multi-segment support
data integration
digital twin model of 5G private network
