An embedding model for temporal knowledge graphs with long and irregular intervals

Author:

Huang HuiminORCID,Xie Luodi,Liu Mingzhe,Lin Jiajun,Shen Hong

Funder

Wenzhou Municipal Science and Technology Bureau

Publisher

Elsevier BV

Reference40 articles.

1. Z. Zhang, J. Cai, Y. Zhang, J. Wang, Learning hierarchy-aware knowledge graph embeddings for link prediction, in: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020, pp. 3065–3072.

2. Z. Sun, Z. Deng, J. Nie, J. Tang, RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space, in: 7th International Conference on Learning Representations, ICLR, 2019.

3. S. Vashishth, S. Sanyal, V. Nitin, P.P. Talukdar, Composition-based Multi-Relational Graph Convolutional Networks, in: 8th International Conference on Learning Representations, 2020.

4. D. Yu, Y. Yang, R. Zhang, Y. Wu, Knowledge embedding based graph convolutional network, in: Proceedings of the Web Conference 2021, 2021, pp. 1619–1628.

5. Leveraging static models for link prediction in temporal knowledge graphs;Radstok,2021

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