面向公众的AI驱动健康教育视频内容推荐系统的设计与优化  

Design and Optimization of an AI-Driven Health Education Video Content Recommendation System for the Public

作　　者：朱虎韬 Zhu Hutao(Hangzhou Knowledge Matrix Information Technology Co.,Ltd.,Hangzhou 310000,China)

机构地区：[1]杭州知识矩阵信息科技有限公司,杭州310000

出　　处：《办公自动化》2025年第7期55-57,共3页Office Informatization

摘　　要：短视频模式的发展极大地推动内容推荐系统的优化,这为健康食品、科普视频等类型的视频推广也构建良好的外部环境。文章就此对互联网媒体跨平台融合背景下的健康教育视频内容推荐系统进行分析,探讨其架构和算法选择,从而说明整体视频内容推荐系统的建设。与此同时,AI技术的优化也为系统建设提供良好的技术支持,深度学习算法能更好地识别用户未能直接标注的视频偏好,通过更为丰富的视频浏览和搜索特征细节补充与完善原有视频内容推荐系统的不足,通过更为丰富的数据化标签适应于用户规模的增长,并相应提升用户体验,且相应优化资源调度能力而提升系统响应速度和实时性,从而为健康教育的个性化发展提供良好环境。The rise of short video platforms has driven significant advancements in content recommendation systems,creating a favorable environment for promoting health-related content such as healthy food and educational science videos.This paper analyzes the design and optimization of a health education video content recommendation system in the context of cross-platform integration of Internet media.It explores the system's architecture,algorithm selection,and overall construction.Meanwhile,advancements in AI technology provide robust technical support for system development.Deep learning algorithms excel at identifying implicit video preferences that users do not explicitly label,addressing and enhancing the limitations of the original video content recommendation system by leveraging richer video browsing and search feature details.These improvements enable the system to scale effectively with growing user numbers,significantly enhancing user experience.Additionally,optimized resource scheduling improves system response speed and real-time performance,thereby fostering a conducive environment for the personalized development of health education.

关 键 词：AI驱动 科普视频 健康教育视频 内容推荐系统 

分 类 号：TP311.52[自动化与计算机技术—计算机软件与理论] G206[自动化与计算机技术—计算机科学与技术] R193[文化科学—传播学]