A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems
《A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems》 目的：矩阵分解是一种广泛使用的基于模型的CF方法具有良好的可扩展性和准确性，asdae利用深度学习从原始输入中有效提取项目和用户潜在信息。这两个模型相结合，来达到预测用户项目评分矩阵的缺失值。 论文信息：携程在深度学习与推荐系统结
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相关文章
- 1. Deep Learning Architecture for Collaborative Filtering Recommender Systems
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