摘要
针对传统教育数据关联挖掘系统存在运行开销大、性能差的问题,设计了基于语义指向性的职业教育数据关联模式挖掘系统。首先,将aServer-E-1800作为挖掘系统的硬件基础,提升系统硬件性能;其次,对原始数据进行量化编码处理;最后进行实验分析。实验结果表明,该系统在不同规模并发请求下中央处理器(Central Processing Unit,CPU)利用率和内存占用率始终稳定在21%以内,优于对照组。
A vocational education data association pattern mining system based on semantic directionality was designed to address the issues of high operating costs and poor performance in traditional education data association mining systems.Firstly,use aServer-E-1800 as the hardware foundation of the mining system to improve system hardware performance.Secondly,the original data is quantized and coded.Finally,conduct experimental analysis.The experimental results show that the Central Processing Unit(CPU)utilization and memory usage of the system remain stable within 21%under different scales of concurrent requests,which is superior to the control group.
作者
冯晟博
FENG Shengbo(School of Information and Media,Inner Mongola Techical College of Construction,Hohhot Inner Mongolia 010000,China)
出处
《信息与电脑》
2023年第12期23-25,共3页
Information & Computer
基金
内蒙古自治区教育科学“十四五”规划课题“基于1+X证书的‘校企联动、课证融通’人才培养模式创新性研究”(项目编号:NZJGH2021010)
新形势下建设类院校新工科专业“课程思政”建设的研究与实践(项目编号:2021249)。
关键词
语义指向性
职业教育数据
关联模式
挖掘
semantic directionality
vocational education data
association mode
excavate