A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems
《A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems》 目的：矩陣分解是一種廣泛使用的基於模型的CF方法具有良好的可擴展性和準確性，asdae利用深度學習從原始輸入中有效提取項目和用戶潛在信息。這兩個模型相結合，來達到預測用戶項目評分矩陣的缺失值。 論文信息：攜程在深度學習與推薦系統結
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相關文章
- 1. Deep Learning Architecture for Collaborative Filtering Recommender Systems
- 2. Collaborative Deep Learning for Recommender Systems
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- 6. Building recommender systems with Azure Machine Learning service
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