计算机应用研究2017，Vol.34Issue(8)：2336-2339,4.DOI:10.3969/j.issn.1001-3695.2017.08.023
基于栈式降噪自编码器的协同过滤算法
Stacked denoising autoencoder for collaborative filtering algorithm
摘要
Abstract
This paper proposed a new method called stacked denoising autoencoder based on collaborative filtering after studying the way of improving precision of recommended algorithm.SDAE was a mul-layer deep learning model which could learn significant dependencies from input information.It used ratings given to items by users to learn the latent feature,got results of dimensionality reduction after PCA to calculate attribute similarities.Then it added the grade similarities computed with concealed feature as the final result.Finally, it emploied similarities between items to generate the top-N recommendation list.Experiments on MovieLens show that the proposed algorithm has higher recall rate and can settle the missing ratings and cold start problems in some way.关键词
推荐系统/协同过滤/深度学习/栈式降噪自编码器Key words
recommender system/collaborative filtering/deep learning/stacked denoising autoencoder(SDAE)分类
信息技术与安全科学引用本文复制引用
周洋,陈家琪..基于栈式降噪自编码器的协同过滤算法[J].计算机应用研究,2017,34(8):2336-2339,4.基金项目
上海市教委科研创新基金资助项目(12zz146) （12zz146）
