PaperReading-TransM《Transition-based Knowledge Graph Embedding with Relational Mapping Properties》

时间 2021-01-13

标签 paperreading 繁體版

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本文记录了TransM《Transition-based Knowledge Graph Embedding with Relational Mapping Properties》的论文阅读，如果有同学在做相关的工作，请通过邮件和我沟通联系[email protected] 背景 TransM算法是基于TransE算法进行的改进，目的还是为了解决在TransE中无法处理的一对多、多对一、多对多和自

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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 解读
4. Recurrent Knowledge Graph Embedding for Eﬀective Recommendation
5. Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
6. Knowledge Graph Embedding：从TransE，TransH到TransR
7. Graph Embedding 、Network Embedding和Knowledge Graph Embedding以及Representation 和Embedding之间的区分
8. EMNLP2019 | Knowledge-Aware Graph Networks
9. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 论文
10. 论文笔记006-《Bootstrapping Entity Alignment with Knowledge Graph Embedding》
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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 解读
4. Recurrent Knowledge Graph Embedding for Eﬀective Recommendation
5. Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
6. Knowledge Graph Embedding：从TransE，TransH到TransR
7. Graph Embedding 、Network Embedding和Knowledge Graph Embedding以及Representation 和Embedding之间的区分
8. EMNLP2019 | Knowledge-Aware Graph Networks
9. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 论文
10. 论文笔记006-《Bootstrapping Entity Alignment with Knowledge Graph Embedding》

>>更多相关文章<<