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
相關文章
- 1. Deep Learning Architecture for Collaborative Filtering Recommender Systems
- 2. Collaborative Deep Learning for Recommender Systems
- 3. An Efficient Deep Learning Approach for Collaborative Filtering Recommender System
- 4. Collaborative filtering with GraphChi
- 5. Wide & Deep Learning for Recommender Systems
- 6. Building recommender systems with Azure Machine Learning service
- 7. Paper Reading:Wide & Deep Learning for Recommender Systems
- 8. A Survey of Recommender Systems Based on Deep Learning （1）
- 9. Wide &Deep Learning for Recommender Systems
- 10. 推薦系統介紹:(協同過濾)—Intro to Recommender Systems: Collaborative Filtering
- 更多相關文章...
- • Scala for循環 - Scala教程
- • Lua for 循環 - Lua 教程
- • RxJava操作符（三）Filtering
- • 爲了進字節跳動，我精選了29道Java經典算法題，帶詳細講解
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
- 1. 融合阿里雲，牛客助您找到心儀好工作
- 2. 解決jdbc(jdbctemplate)在測試類時不報錯在TomCatb部署後報錯
- 3. 解決PyCharm GoLand IntelliJ 等 JetBrains 系列 IDE無法輸入中文
- 4. vue+ant design中關於圖片請求不顯示的問題。
- 5. insufficient memory && Native memory allocation (malloc) failed
- 6. 解決IDEA用Maven創建的Web工程不能創建Java Class文件的問題
- 7. [已解決] Error: Cannot download ‘https://start.spring.io/starter.zip?
- 8. 在idea讓java文件夾正常使用
- 9. Eclipse啓動提示「subversive connector discovery」
- 10. 帥某-技巧-快速轉帖博主文章（article_content）
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Deep Learning Architecture for Collaborative Filtering Recommender Systems
- 2. Collaborative Deep Learning for Recommender Systems
- 3. An Efficient Deep Learning Approach for Collaborative Filtering Recommender System
- 4. Collaborative filtering with GraphChi
- 5. Wide & Deep Learning for Recommender Systems
- 6. Building recommender systems with Azure Machine Learning service
- 7. Paper Reading:Wide & Deep Learning for Recommender Systems
- 8. A Survey of Recommender Systems Based on Deep Learning （1）
- 9. Wide &Deep Learning for Recommender Systems
- 10. 推薦系統介紹:(協同過濾)—Intro to Recommender Systems: Collaborative Filtering