深度学习技术在个性化推荐系统中的应用与发展综述  

Comprehensive review of development of deep learning technology and personalized recommendation systems

作　　者：郭秋叶 GUO Qiuye(Guangzhou Vocational College of Technology&Business,Guangzhou 511442,China;Youngsan University,Yangsan 50510,Republic of Korea)

机构地区：[1]广州科技贸易职业学院,广州511442 [2]灵山大学,韩国梁山50510

出　　处：《计算机应用文摘》2024年第24期157-160,共4页

基　　金：广州科技贸易职业学院科研项目青年专项:个性化推荐技术在融媒体内容创作中的应用研究(2024QN06)。

摘　　要：文章综述了基于深度学习的个性化推荐系统在新媒体平台短视频内容推荐中的应用。首先,介绍了个性化推荐系统的基本原理及发展历程,并分析了传统推荐算法的局限性。其次,深入探讨了深度学习技术的基本原理、主要模型架构及其在推荐系统中的应用场景。通过分析相关案例,文章详细讨论了基于深度学习的个性化推荐系统在新媒体平台短视频推荐中的关键技术和面临的挑战。最后,展望了未来的研究方向,指出了基于深度学习的个性化推荐系统在提高推荐准确性、多样性和用户体验等方面的潜力。The article summarizes the application of personalized recommendation systems based on deep learning in short video content recommendation on new media platforms.Firstly,the basic principles and development history of personalized recommendation systems were introduced,and the limitations of traditional recommendation algorithms were analyzed.Secondly,the basic principles,main model architectures,and application scenarios of deep learning technology in recommendation systems were explored in depth.By analyzing relevant cases,the article discusses in detail the key technologies and challenges faced by personalized recommendation systems based on deep learning in short video recommendation on new media platforms.Finally,future research directions were discussed,and the potential of personalized recommendation systems based on deep learning in improving recommendation accuracy,diversity,and user experience was pointed out.

关 键 词：个性化推荐系统 深度学习 新媒体平台 短视频内容 推荐准确性 推荐多样性 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]