HierarT: Multi-hop temporal knowledge graph forecasting with hierarchical reinforcement learning-Reference-Cited by-同舟云学术

HierarT: Multi-hop temporal knowledge graph forecasting with hierarchical reinforcement learning

Published:2024-09 Issue: Volume:300 Page:112164
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Luo Xuewei^ORCID,Zhu Anjie^ORCID,Zhang Jiasheng^ORCID,Shao Jie^ORCID

Publisher

Elsevier BV

Reference42 articles.

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2. Path-based multi-hop reasoning over knowledge graph for answering questions via adversarial reinforcement learning;Cui;Knowl.-Based Syst.,2023

3. X. Wang, D. Wang, C. Xu, X. He, Y. Cao, T. Chua, Explainable Reasoning over Knowledge Graphs for Recommendation, in: The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, 2019, pp. 5329–5336.

4. T. Jiang, T. Liu, T. Ge, L. Sha, B. Chang, S. Li, Z. Sui, Towards Time-Aware Knowledge Graph Completion, in: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, December 11-16, 2016, Osaka, Japan, 2016, pp. 1715–1724.

5. S.S. Dasgupta, S.N. Ray, P.P. Talukdar, HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding, in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31 - November 4, 2018, 2018, pp. 2001–2011.