在线体育视频教学资源的精准推荐算法

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2022-10-26 DOI:10.4108/eetsis.v10i1.2578

Xu Zhu, Zhao Zhang

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引用次数: 1

摘要

导读:随着疫情的发展，网络教学逐渐成为热门话题。然而，与传统教学项目不同的是，体育资源种类繁多，相关内容的推荐一直是网络教学的难点。目的:为此，本文设计了一种体育在线视频教学资源的精准推荐算法，以满足体育专业在线学习的个性化需求。整个推荐算法的数据层将视频存储在数据库中，接收到数据后发送给业务处理层。方法:本研究采用社会网络分析技术进行。推荐算法的数据层接收到数据后，将视频存储在数据库中，同时传输给业务处理层。业务处理层使用设计的协同过滤资源推荐算法，针对不同用户制定推荐结果，并将推荐结果推送到用户层的用户显示界面。结果:算法的测试结果表明，所设计的系统具有较高的推荐成功率，当并发用户数为500时，系统仍能保持稳定的运行性能。该方法资源推荐的平均准确率为98.21%，平均召回率为98.35%，平均F1值为95.37%。结论:本文提出的资源推荐算法通过高效的推荐算法，实现了体育在线视频教学资源的精准推荐。

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Precise Recommendation Algorithm for Online Sports Video Teaching Resources

INTRODUCTION: With the development of the epidemic, online teaching has gradually become a hot topic. However, unlike traditional teaching programs, there are many types of physical education resources, and the recommendation of related content has always been a difficulty in online teaching. OBJECTIVES: Therefore, this paper designs an accurate recommendation algorithm for online video teaching resources of sports to meet the personalized needs of online learning of sports majors. The data layer of the entire recommendation algorithm stores the video in the database and transmits it to the service processing layer after receiving the data. METHODS: This study was conducted using techniques from social network analysis. After receiving the data, the data layer of the recommendation algorithm stores the video in the database and transmits it to the business processing layer at the same time. The business processing layer uses the designed collaborative filtering resource recommendation algorithm to formulate recommendation results for different users, and push the recommended results to the user display interface of the user layer. RESULTS: The test results of the algorithm show that the designed system has a high recommendation success rate, and the system can still maintain stable running performance when the concurrent users are 500. The average precision of resource recommendation of this method is 98.21%, the average recall rate is 98.35%, and the average F1 value is 95.37%. CONCLUSION: The proposed resource recommendation algorithm realizes accurate recommendation of sports online video teaching resources through efficient recommendation algorithms.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.