摘要
由于现有的高等教育弹性资源推荐系统处理高等教育弹性资源的速度慢,系统性能差,为此设计基于协同过滤的高等教育弹性资源推荐系统。首先,使用芯片为TYD-DSPX的处理器处理系统采集的信号,通过外部存储器接口(External Memory Interface,EMIF)调入请求的缓存数据,将随机存取存储器(Random Access Memory,RAM)数据实时传输到中央处理器(Central Processing Unit,CPU)中;其次,整合学习者与学习资源数据,对高等教育弹性资源进行相似度计算并赋予权重;最后,设定时间填充函数,分析并计算用户对资源的偏好程度,从而完成相关资源精准推荐。测试结果表明,在相同场景下,输入数据查询条件后,20个小组的资源推荐更新处理数据速度均在3 s内,满足设计预期。
Because the existing elastic resources recommendation system of higher education is slow to process the elastic resources of higher education,and the system performance is poor,a higher education elastic resources recommendation system based on Collaborative filtering is designed.Firstly,use the TYD-DSPX processor to process the signals collected by the system,call in the requested cache data through the External Memory Interface(EMIF),and transmit the Random Access Memory(RAM)data to the Central Processing Unit(CPU)in real time.Secondly,integrate learner and learning resource data,calculate the similarity of higher education elastic resources and assign weights.Finally,set a time flling function to analyze and calculate the user's preference for resources,in order to achieve accurate recommendation of related resources.The test results show that in the same scenario,after inputting data query conditions,the resource recommendation update processing speed of 20 groups is all within 3 seconds,meeting the design expectations.
作者
张磊
ZHANG Lei(Jilin Railway Technology College,Jilin Jilin 132000,China)
出处
《信息与电脑》
2023年第10期254-256,共3页
Information & Computer
基金
吉林省高等教育学会“应对重大突发事件的高等教育弹性教学模式研究”(项目编号:JGJX2022D717)。
关键词
协同过滤
教育
弹性资源
推荐
collaborative filtering
education
flexible resources
recommendation
