Knowledge Graph Embedding via Dynamic Mapping Matrix
@inproceedings{Ji2015KnowledgeGE, title={Knowledge Graph Embedding via Dynamic Mapping Matrix}, author={Guoliang Ji and Shizhu He and L. Xu and Kang Liu and Jun Zhao}, booktitle={ACL}, year={2015} }
Knowledge graphs are useful resources for numerous AI applications, but they are far from completeness. [...] Key Method In this paper, we propose a more fine-grained model named TransD, which is an improvement of TransR/CTransR. In TransD, we use two vectors to represent a named symbol object (entity and relation). The first one represents the meaning of a(n) entity (relation), the other one is used to construct mapping matrix dynamically.Expand Abstract
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References
SHOWING 1-10 OF 21 REFERENCES
Learning Entity and Relation Embeddings for Knowledge Graph Completion
- Computer Science
- AAAI
- 2015
- 1,319
- Highly Influential
- PDF
Knowledge Graph Embedding by Translating on Hyperplanes
- Computer Science
- AAAI
- 2014
- 1,279
- Highly Influential
Translating Embeddings for Modeling Multi-relational Data
- Computer Science, Mathematics
- NIPS
- 2013
- 2,557
- Highly Influential
- PDF
Reasoning With Neural Tensor Networks for Knowledge Base Completion
- Computer Science
- NIPS
- 2013
- 1,285
- Highly Influential
- PDF
A semantic matching energy function for learning with multi-relational data
- Computer Science
- Machine Learning
- 2013
- 409
- Highly Influential
- PDF
A Review of Relational Machine Learning for Knowledge Graphs
- Computer Science, Mathematics
- Proceedings of the IEEE
- 2016
- 850
- PDF