Lapis-Hong / TransE-Knowledge-Graph-Embedding

TensorFlow implementation of TransE and its extended models for Knowledge Representation Learning

Knowledge-Grapth-Embedding

Knowledge Graph Embedding model collections implemented by TensorFlow. Including TransE [1], TransH [2], TransR [3], TransD [4] models for knowledge representation learning (KRL).

Prerequisites

• Python 3.6
• TensorFlow 1.10

Data

You can download FB15K and WN18 from Download.

TODO

add more models

Usage

python train.py

References

[1] Bordes, Antoine, et al. Translating embeddings for modeling multi-relational data. Proceedings of NIPS, 2013.

[2] Zhen Wang, Jianwen Zhang, et al. Knowledge Graph Embedding by Translating on Hyperplanes. Proceedings of AAAI, 2014.

[3] Yankai Lin, Zhiyuan Liu, et al. Learning Entity and Relation Embeddings for Knowledge Graph Completion. Proceedings of AAAI, 2015.

[4] Guoliang Ji, Shizhu He, et al. Knowledge Graph Embedding via Dynamic Mapping Matrix. Proceedings of ACL, 2015.