#Paper Reading# RippleNet: Propagating User Preferences on the KG for Recommender Systems
論文題目: RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems 論文地址: https://dl.acm.org/citation.cfm?id=3271739 論文發表於: CIKM 2018（CCF B類會議） 論文大體內容： 本文主要介紹了一種通過引入Knowledge
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相關文章
- 1. 閱讀筆記--RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems
- 2. RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems簡析
- 3. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 4. Paper Reading:Wide & Deep Learning for Recommender Systems
- 5. #Paper Reading# Personalized Context-aware Re-ranking for E-commerce Recommender Systems
- 6. paper review : Multimodal data fusion framework based on autoencoders for top-N recommender systems
- 7. #Paper Reading# xDeepFM:Combining Explicit and Implicit Feature Interactions for Recommender Systems
- 8. Paper Notes: Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommenda
- 9. Side Information-Knowledge Graph Convolutional Networks for Recommender Systems閱讀筆記
- 10. #Paper Reading# On the Measure of Intelligence