首页|基于深度学习的短视频智能推荐算法技术

基于深度学习的短视频智能推荐算法技术

扫码查看
采用目前方法对短视频进行智能推荐时,没有对用户的长短期喜好分别进行考虑,导致点击率和推荐准确率低、综合推荐效果差的问题.提出基于深度学习的短视频智能推荐算法技术,首先提取目标短视频的场景特征和行为特征,从而得到联合特征,然后采用深度学习分别对用户的长短期喜好进行建模分析,最后结合目标短视频的联合特征和用户短视频喜好特征计算相似度和喜好度,选取喜好度最高的若干短视频构成推荐列表,完成短视频的智能推荐.实验结果表明,所提方法具有更高的点击率、推荐准确率和更好的综合推荐效果.
Short video intelligent recommendation algorithm technology based on deep learning
When using the current method to intelligently recommend short videos,the user's long-and short-term preferences are not considered separately,which leads to the problems of low click-through rate and recommendation accuracy,as well as the poor comprehensive recommendation effects.Therefore,a short video intelligent recommendation algorithm technology based on deep learning is proposed.Firstly,the scene features and behavior features of the target short video are extracted to obtain joint features.Then,deep learning are used to model and analyze the user's long and short-term preferences.Finally the similar-ity and preference are calculated by joint features of the target short video and the the joint features of the user's short video preference,and several short videos with the highest preference are selected to form a recommendation list to complete the intelligent recommendation of short videos.The experiment results show that the proposed method has higher click-through rate,recommendation accuracy rate and better compre-hensive recommendation effect.

deep learningshort videointelligent recommendationinter-frame matching methodgraph convolutional neural network

徐缤荣

展开 >

西安欧亚学院,西安 710000

深度学习 短视频 智能推荐 帧间匹配法 图卷积神经网络

2024

信息技术
黑龙江省信息技术学会 中国电子信息产业发展研究院 中国信息产业部电子信息中心

信息技术

CSTPCD
影响因子:0.413
ISSN:1009-2552
年,卷(期):2024.(2)
  • 12