Learning over Knowledge-Base Embeddings for Recommendation 論文
Paper-CFKG 中心思想：通過知識表示學習方法來嵌入異質實體來進行推薦。 文章定義了一個 用戶-物品知識圖 的概念（user-item knowledge graph），藉此擴展原來的協同過濾（collaborative filtering） MODEL：COLLABORATIVE FILTERING WITH KNOWLEDGE-GRAPH we first define a
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相關文章
- 1. 論文筆記：Personalized Deep Learning for Tag Recommendation
- 2. 論文筆記 GAME:Learning Graphical and Attentive Multi-view Embeddings for Occasional Group Recommendation
- 3. Explainable Reasoning over Knowledge Graphs for Recommendation
- 4. #Paper Reading# Deep Learning Recommendation Model for Personalization and Recommendation Systems
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- 6. 論文淺嘗 | Complex Embeddings for Simple Link Prediction
- 7. 論文筆記：ACL 2019 Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
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- 9. 論文筆記：AAAI 2020 Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
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