【論文理解】Graph Neural News Recommendation with Unsupervised Preference Disentanglement
本片論文是2020中國入選ACL的論文之一，是北郵計算機學院圖數據挖掘和機器學習實驗室的石川老師等和微軟亞洲研究院合作完成的項目，我簡單拜讀了一下，寫一點自己的淺薄理解，如有不對還請指出！ 1. 基本要素 新聞推薦核心：如何更好的瞭解用戶和新聞的表徵。 consider high- order connectivity underlying the user-news interactions：一
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相關文章
- 1. 推薦系統論文：Neural News Recommendation with Attentive Multi-View Learning
- 2. 推薦系統論文筆記---Neural News Recommendation with Attentive Multi-View Learning
- 3. GNN:Session-based Recommendation with Graph Neural Networks簡介
- 4. Graph Neural Networks for Social Recommendation
- 5. Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks論文理解
- 6. 【論文解讀 KDD 2019 | MEIRec】Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation
- 7. Neural News Recommendation with Long- and Short-term User Representation（LSTUR)
- 8. 論文筆記——News Recommendation with Topic-Enriched Knowledge Graphs
- 9. 【SR-GNN】Session-based Recommendation with Graph Neural Networks詳解
- 10. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph