[1]李文欣,文勇军,唐立军.教育资源个性化推荐方法研究与实现[J].计算机技术与发展,2019,29(06):18-22.[doi:10. 3969 / j. issn. 1673-629X. 2019. 06. 004]
　LI Wen-xin,WEN Yong-jun,TANG Li-jun.Research and Implementation of Personalized Recommendation Method for Educational Resources[J].,2019,29(06):18-22.[doi:10. 3969 / j. issn. 1673-629X. 2019. 06. 004]
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教育资源个性化推荐方法研究与实现()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年06期
页码:
18-22
栏目:
智能、算法、系统工程
出版日期:
2019-06-10

文章信息/Info

Title:
Research and Implementation of Personalized Recommendation Method for Educational Resources
文章编号:
1673-629X(2019)06-0018-05
作者:
李文欣1; 2 ; 文勇军1; 2 ; 唐立军1; 2
1. 长沙理工大学 物理与电子科学学院,湖南 长沙 410114;2. 长沙理工大学 近地空间电磁环境监测与建模湖南省普通高校重点实验室, 湖南 长沙 410114
Author(s):
LI Wen-xin 1; 2 ; WEN Yong-jun 1; 2 ; TANG Li-jun 1; 2
1. School of Physical &Electric Science,Changsha University of Science &Technology,Changsha 410114,China; 2. Hunan Province Higher Education Key Laboratory of Modeling and Monitoring on the Near-Earth Electromagnetic Environments,Changsha University of Science &Technology,Changsha 410114,China
关键词:
教育资源; 网络爬虫; 个性化推荐; 预测模型
Keywords:
educational resources; Web crawler; personalized recommendation; predictive model
分类号:
TP311
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 06. 004
摘要:
随着教育信息化的快速发展,网络教育资源的开发得到了国内外的高度重视,各类教育资源信息更新速度惊人。为避免教育资源浪费,提高查找效率,及时为用户推荐有效信息资料,运用 Java Web 开发技术,结合网络爬虫技术和预测算法分析方法,设计实现了教育资源个性化推荐系统。 系统采用 Java 爬虫技术,获取特定教育资源网站上公开教育资源信息,作为系统研究数据来源;采用矩阵分解模型、多层感知机模型和 NeuMF 预测分析模型,分析处理用户特征值矩阵和教育资源特征值矩阵,关联用户特征信息与教育资源信息,得到用户-教育资源预测值;研究教育资源个性化推荐技术,按照预测值优先级,将符合用户需求的教育资源信息推荐给 Web 用户。 经测试,系统运行稳定可靠,资源推荐率大于 80%,资源推荐覆盖率广、推荐性强、实时性好、质量高,可以为用户提供及时的资源推荐服务,大大提高了教育资源的查找效率和资源利用率。
Abstract:
With the rapid development of education informatization,the development of network education resources has been highly valued at home and abroad. The information updating speed of all kinds of education resources is astonishing. In order to avoid waste of education resources,improve search efficiency,and timely recommend effective information materials for users,we design and implement a personalized recommendation system for educational resources by Java Web development technology in combination with network crawler technology and advance. The system uses Java crawler technology to obtain the information of public educational resources on specific educational resources websites as the data source of the system research,and uses matrix decomposition model,multi-layer perception model and NeuMF predictive analysis model to analyze and process user eigenvalue matrix and education resources eigenvalue matrix and correlate user information and educational resources information for user - education resources predictive value. The personalized recommendation technology of educational resources is studied. According to the priority of predictive value,the education resources information that meets the user needs is recommended to Web users. The system has been tested to be stable and reliable,with a resource recommendation rate of more than 80%. With wide coverage,strong recommendation,great real-time performance and high quality,it can provide users with timely resource recommendation services,greatly improving the search efficiency and resource utilization rate of educational resources.

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更新日期/Last Update: 2019-06-10