PaperReading-TransM《Transition-based Knowledge Graph Embedding with Relational Mapping Properties》
本文記錄了TransM《Transition-based Knowledge Graph Embedding with Relational Mapping Properties》的論文閱讀，如果有同學在做相關的工作，請通過郵件和我溝通聯繫[email protected] 背景 TransM算法是基於TransE算法進行的改進，目的還是爲了解決在TransE中無法處理的一對多、多對一、多對多和自
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相關文章
- 1. 【PaperReading】Knowledge Graph Embedding Based Question Answering
- 2. Embedding Multimodal Relational Data for Knowledge Base Completion理解
- 3. convolutional 2D knowledge graph embedding 解讀
- 4. Recurrent Knowledge Graph Embedding for Effective Recommendation
- 5. Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
- 6. Knowledge Graph Embedding：從TransE，TransH到TransR
- 7. Graph Embedding 、Network Embedding和Knowledge Graph Embedding以及Representation 和Embedding之間的區分
- 8. EMNLP2019 | Knowledge-Aware Graph Networks
- 9. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 論文
- 10. 論文筆記006-《Bootstrapping Entity Alignment with Knowledge Graph Embedding》