| 尹婷婷,龚思怡,曾宪玉.基于用户画像技术的教育资源个性化推荐服务研究[J].数字图书馆论坛,2019,(11):29~35 |
| 基于用户画像技术的教育资源个性化推荐服务研究 |
| Research on Personalized Recommendation Service for Educational Resources Based on User Profile |
| 投稿时间：2019-10-20 |
| DOI：10.3772/j.issn.1673-2286.2019.11.004 |
| 中文关键词: 用户画像；教育资源；个性化推荐 |
| 英文关键词: User Profile; Educational Resources; Personalized Recommendation Service |
| 基金项目:本研究得到陕西省教育厅专项科研计划项目“基于多约束凸优化的图书馆文献购置经费分配研究”（编号：14JK1497）和中央高校基本科研业务项目“‘双一流’建设背景下我校青年教师教学胜任力提升机制研究”（编号：2018ZCY16）资助。 |
| 作者 | 单位 | | 尹婷婷 | 西北工业大学教务处 | | 龚思怡 | 西北工业大学教务处 | | 曾宪玉 | 西北工业大学图书馆 |
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| 中文摘要: |
| 用户画像作为“互联网+”环境下针对学习者个性化信息分析及教育资源推荐服务设计工具，为教育资源个性化推荐服务提供了新的研究思路。针对用户画像的具体应用及教育资源个性化推荐服务现状进行概述与归纳；在大数据背景下构建由数据基础层、数据处理层、数据挖掘层组成的教育资源个性化推荐服务模型；分别从优化教育资源个性化推送、开展学习者群体服务、提供个性化学习路径导航服务等具体层面，提出并设计基于用户画像的教育资源个性化推荐服务的应用模式，以期为高校开展教育资源个性化推荐服务和满足学习者多粒度个性化学习需求提供参考依据。 |
| 英文摘要: |
| As the powerful tool for analysis of learners’ individual resource needs and push service design of educational resources under the background of “Internet +” information age, user profile technology provides new research approach for personalized recommendation service for educational resources. The application practice of user profile technology and the development status of personalized recommendation service for educational resources are generalization and induction. Based on user profile technology, the three-layer personalized recommendation service for educational resources model is established which is consisting of data source layer, data analysis integration layer and data mining layer in the context of big data. From the specific aspects of optimizing the push of personalized learning resources, developing group services for learners, providing personalized learning path navigation services, the application mode of personalized recommendation service for educational resources is discussed and analyzed based on user profile technology, in order to provide reference for carrying out the personalized recommendation service of educational resources and meeting the multi granularity personalized learning needs of learners under the background of big data. |
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