Implicit relational attention network for few-shot knowledge graph completion
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Zhejiang Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05511-0.pdf
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3. Chen M, Zhang W, Zhang W, Chen Q, Chen H (2019) Meta relational learning for few-shot link prediction in knowledge graphs. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). pp. 4217–4226
4. Finn C, Abbeel P, Levine S (2017) Model-agnostic meta-learning for fast adaptation of deep networks. In: International conference on machine learning. pp. 1126–1135
5. Geng Y, Chen J, Pan JZ, Chen M, Jiang S, Zhang W, Chen H (2023) Relational message passing for fully inductive knowledge graph completion. In: 2023 IEEE 39th International Conference on Data Engineering (ICDE). pp. 1221–1233
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