mlsanityData to 14 Oct 2026

Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs

arXiv 1705.05742 ↗First posted 16 May 2017cs.AI cs.CL cs.LGcited by 149

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Abstract (arXiv)

The availability of large scale event data with time stamps has given rise to dynamically evolving knowledge graphs that contain temporal information for each edge. Reasoning over time in such dynamic knowledge graphs is not yet well understood. To this end, we present Know-Evolve, a novel deep evolutionary knowledge network that learns non-linearly evolving entity representations over time. The occurrence of a fact (edge) is modeled as a multivariate point process whose intensity function is modulated by the score for that fact computed based on the learned entity embeddings. We demonstrate significantly improved performance over various relational learning approaches on two large scale real-world datasets. Further, our method effectively predicts occurrence or recurrence time of a fact which is novel compared to prior reasoning approaches in multi-relational setting.

Key facts. Cited by 149 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 May 2017.

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Citing papers per year: 2021: 35; 2022: 31; 2023: 30; 2024: 23; 2025: 7; 2026: 23.

149 papers.

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  1. 2021Inductive Representation Learning in Temporal Networks via Causal Anonymous Walkscited by 193
  2. 2022ROLAND: Graph Learning Framework for Dynamic Graphscited by 132
  3. 2021Neural Temporal Point Processes: A Reviewcited by 114
  4. 2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 110
  5. 2021Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learningcited by 106
  6. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  7. 2024Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generationcited by 80
  8. 2021Complex Temporal Question Answering on Knowledge Graphscited by 69
  9. 2021TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecastingcited by 67
  10. 2021Temporal Knowledge Graph Forecasting with Neural ODEcited by 61
  11. 2022Temporal Knowledge Graph Completion: A Surveycited by 61
  12. 2023Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunitiescited by 61
38 more
  1. 2021A Survey on Embedding Dynamic Graphscited by 60
  2. 2021Neuro-Symbolic Artificial Intelligence: Current Trendscited by 54
  3. 2022Neighborhood-aware Scalable Temporal Network Representation Learningcited by 54
  4. 2023Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoningcited by 45
  5. 2021Dynamic Network Embedding Surveycited by 44
  6. 2022Temporal Knowledge Graph Reasoning with Historical Contrastive Learningcited by 42
  7. 2021Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphscited by 39
  8. 2022Reinforced Structured State-Evolution for Vision-Language Navigationcited by 37
  9. 2021Knowledge Enhanced Pretrained Language Models: A Compreshensive Surveycited by 33
  10. 2024A Survey on Temporal Knowledge Graph: Representation Learning and Applicationscited by 30
  11. 2024A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challengescited by 30
  12. 2022EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphscited by 27
  13. 2022Subgraph Neighboring Relations Infomax for Inductive Link Prediction on Knowledge Graphscited by 27
  14. 2021Spatio-Temporal Urban Knowledge Graph Enabled Mobility Predictioncited by 24
  15. 2024A survey of dynamic graph neural networkscited by 24
  16. 2023TEILP: Time Prediction over Knowledge Graphs via Logical Reasoningcited by 23
  17. 2022Graph Neural Networks Designed for Different Graph Types: A Surveycited by 21
  18. 2022Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphscited by 21
  19. 2021What is Event Knowledge Graph: A Surveycited by 19
  20. 2024Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Modelscited by 17
  21. 2023AutoSeqRec: Autoencoder for Efficient Sequential Recommendationcited by 15
  22. 2022Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Surveycited by 14
  23. 2023A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospectscited by 14
  24. 2022TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graphcited by 13
  25. 2021Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvaturescited by 12
  26. 2022Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphscited by 12
  27. 2022Parameter-free Dynamic Graph Embedding for Link Predictioncited by 12
  28. 2023Triple Structural Information Modelling for Accurate, Explainable and Interactive Recommendationcited by 12
  29. 2023DistTGL: Distributed Memory-Based Temporal Graph Neural Network Trainingcited by 12
  30. 2021Efficient Scaling of Dynamic Graph Neural Networkscited by 11
  31. 2021Lifelong Learning on Evolving Graphs Under the Constraints of Imbalanced Classes and New Classescited by 11
  32. 2023On the Evolution of Knowledge Graphs: A Survey and Perspectivecited by 10
  33. 2023HGE: Embedding Temporal Knowledge Graphs in a Product Space of Heterogeneous Geometric Subspacescited by 10
  34. 2024Chain of History: Learning and Forecasting with LLMs for Temporal Knowledge Graph Completioncited by 10
  35. 2024Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Predictioncited by 10
  36. 2021Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learningcited by 9
  37. 2022RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completioncited by 9
  38. 2022Robust Knowledge Adaptation for Dynamic Graph Neural Networkscited by 9

50 most cited of 149 All 149 (JSON)