2019_NAACL_A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Persona
代码地址：https://github.com/daiquocnguyen/CapsE 摘要 本文提出一种嵌入模型，名为CapsE，用胶囊网络建模三元组关系。 用一个三列的矩阵表示每个三元组，每列表示三元组(subject, relation, object)中的一个元素。然后将这个三列的矩阵喂给卷积层，用不同的卷积核生成不同的feature map，输入胶囊网络进行打分操作。有效的三元组分数很高
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相关文章
- 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 论文
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- 6. 论文解析：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
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