Machine learningNetwork science
时序知识图谱分析
时序知识图谱分析将标准知识图谱方法扩展到事实和关系带有时间戳或有效性区间的数据。它能够推理实体和关系如何随时间演变，支持未来事实的链接预测、时序关系分类以及动态关系数据中的事件预测等任务。
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来源
- Trivedi, R., Dai, H., Wang, Y., & Song, L. (2017). Know-Evolve: Deep temporal reasoning for dynamic knowledge graphs. Proceedings of the 34th International Conference on Machine Learning (ICML), pp. 3462–3471. link ↗
- Dasgupta, S. S., Ray, S. N., & Talukdar, P. (2018). HyTE: Hyperplane-based temporally aware knowledge graph embedding. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 2001–2011. DOI: 10.18653/v1/D18-1225 ↗
如何引用本页
ScholarGate. (2026, June 3). Temporal Knowledge Graph Analysis (TKG Analysis). ScholarGate. https://scholargate.app/zh/network-analysis/temporal-knowledge-graph-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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