现代电子技术2024，Vol.47Issue(20)：95-100,6.DOI:10.16652/j.issn.1004-373x.2024.20.015
基于神经网络和注意力机制的协同过滤推荐算法的研究
Research on collaborative filtering recommendation algorithm based on neural network and attention mechanism
摘要
Abstract
In order to solve the problem that the sparseness of the user-item matrix in the collaborative filtering recommendation algorithm can cause poor recommendation degree of the traditional collaborative filtering algorithm,an improved collaborative filtering recommendation algorithm B-SDAECF based on neural network and attention is proposed to solve the problem of data sparsity in the traditional recommendation system.By combining the transformer Bert model of the Transformer model and the stacked denoise auto-encoder(SDAE),the Bert model is used to extract high-quality feature representations from user reviews to obtain the vector matrix.The vector matrix is used as the initial weight of the SDAE,so that the SDAE model can be operated more quickly,and then the original user-item scoring matrix is filled.The experimental results show that,in comparison with the traditional method,the proposed method can significantly improve the accuracy and robustness of the recommendation system,and has better recommendation performance.关键词
神经网络/注意力机制/协同过滤/推荐系统/Bert模型/SDAEKey words
neural network/attention mechanism/collaborative filtering/recommendation system/Bert model/SDAE分类
电子信息工程引用本文复制引用
王宁,李然,王客程,吴江,范利利..基于神经网络和注意力机制的协同过滤推荐算法的研究[J].现代电子技术,2024,47(20):95-100,6.基金项目
中国医药教育协会2022重大科学攻关问题和医药技术难题重点课题(2022KTM036) （2022KTM036）
