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Temporal Knowledge Graph Analysis

Temporal Knowledge Graph Analysis extends standard knowledge graph methods to data where facts and relationships carry timestamps or validity intervals. It enables reasoning about how entities and relations evolve over time, supporting tasks such as link prediction for future facts, temporal relation classification, and event forecasting in dynamic relational data.

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Sources

  1. 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 ↗
  2. 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 ↗

Related methods

Knowledge Graph AnalysisMultilayer Knowledge Graph AnalysisTemporal Community DetectionTemporal Network Diffusion AnalysisTemporal Social Network Analysis

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ScholarGate — Temporal Knowledge Graph Analysis (Temporal Knowledge Graph Analysis (TKG Analysis)). Retrieved 2026-06-04 from https://scholargate.app/tr/network-analysis/temporal-knowledge-graph-analysis