摘要
由于传统系统存在新用户推荐及推荐效果较差的问题,提出一种基于数据挖掘的思政理论资源个性化推荐系统。硬件中服务器模块共由22台服务器构成。处理器模块选用的是S3C3210x处理器。软件中数据挖掘模块主要利用Orange工具箱来实现思政理论资源的数据挖掘。数据处理模块能够实现资源数据的转换与爬取、降维处理。资源个性化推荐模块主要通过混合推荐技术实现个性化推荐。数据库模块中包括用户兴趣表、资源信息表、用户信息表。以此进行性能测试。实验结果表明,其推荐效果优于传统系统,可实现新用户的个性化推荐。
Due to the poor performance of the traditional system in new user recommendation and recommendation, a data mining-based ideological and political theory resource personalized recommendation system is proposed. The server module in the hardware consists of 22 servers. What the processor module chooses is S3C3210x processor. The data mining module in the software mainly uses the Orange toolbox to realize the data mining of ideological and political theory resources. The data processing module can realize the conversion and crawling of resource data, and the processing of dimensionality reduction. The resource personalized recommendation module mainly implements the resource personalized recommendation through hybrid recommendation technology.The database module includes a user interest table, a resource information table, and a user information table. To perform performance testing. Experimental results show that its recommendation effect is better than that of traditional systems, and it can achieve personalized recommendations for new users.
作者
杨志鹏
刘雪雪
YANG Zhi-peng;LIU Xue-xue(Shaanxi Railway Institute,Weinan 714000 China)
出处
《自动化技术与应用》
2023年第1期93-96,共4页
Techniques of Automation and Applications
基金
陕西省2022年高校学生工作精品项目(2022XXM17)
陕西省2021年铁路工程职业技术学院科研基金项目(KY2021-50)
中华职业教育社第一届黄炎培职业教育思想研究规划课题(ZJS2022YB175)
陕西铁路工程职业技术学院2022年辅导员工作精品项目(2022fd-01)。
