【摘要】 最近这几年,随着深度学习快速发展,在图像处理、自然语言处理等领域有了很多应用,而在推荐系统领域,深度学习的应用还不是很常见,并且现在传统的推荐算法也遇到了一些瓶颈,由于现在的评分数据非常稀疏,传统的矩阵分解模型,在一些评分预测领域效果不是很理想。本论文为了解决这些问题,提出一种基于深度学习的个性化推荐算法,考虑利用深度学习来解决评分预测不准的问题。更多还原

【Abstract】 In recent years, with the rapid development of deep learning, there are a lot of applications in image processing, natural language processing and other fields, but in the field of recommender system, the application of deep learning is not very common. And the traditional recommendation algorithm has encountered some bottlenecks, since the scoring data is very sparse, the traditional matrix decomposition model is not very effective in some field of scoring prediction. In order to solve these problems, this paper proposes a personalized recommendation algorithm based on deep learning, which considers the use of deep learning to solve the problem of scoring prediction inaccuracy.更多还原