2019_NAACL_A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Persona
代碼地址：https://github.com/daiquocnguyen/CapsE 摘要 本文提出一種嵌入模型，名爲CapsE，用膠囊網絡建模三元組關係。 用一個三列的矩陣表示每個三元組，每列表示三元組(subject, relation, object)中的一個元素。然後將這個三列的矩陣餵給卷積層，用不同的卷積核生成不同的feature map，輸入膠囊網絡進行打分操作。有效的三元組分數很高
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相關文章
- 1. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 2. Recurrent Knowledge Graph Embedding for Effective Recommendation
- 3. Embedding Multimodal Relational Data for Knowledge Base Completion理解
- 4. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 論文
- 5. NASE Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 閱讀筆記
- 6. 論文解析：NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search
- 7. PaperReading-TransR,《Learning Entity and Relation Embeddings for Knowledge Graph Completion
- 8. 【PaperReading】Knowledge Graph Embedding Based Question Answering
- 9. embedding entities and relations for learning and inference knowledge base
- 10. convolutional 2D knowledge graph embedding 解讀