mlsanityData to 14 Oct 2026

Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs

arXiv 1905.04914 ↗First posted 13 May 2019cs.AI cs.CL cs.LGcited by 83

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Abstract (arXiv)

We study the problem of knowledge graph (KG) embedding. A widely-established assumption to this problem is that similar entities are likely to have similar relational roles. However, existing related methods derive KG embeddings mainly based on triple-level learning, which lack the capability of capturing long-term relational dependencies of entities. Moreover, triple-level learning is insufficient for the propagation of semantic information among entities, especially for the case of cross-KG embedding. In this paper, we propose recurrent skipping networks (RSNs), which employ a skipping mechanism to bridge the gaps between entities. RSNs integrate recurrent neural networks (RNNs) with residual learning to efficiently capture the long-term relational dependencies within and between KGs. We design an end-to-end framework to support RSNs on different tasks. Our experimental results showed that RSNs outperformed state-of-the-art embedding-based methods for entity alignment and achieved competitive performance for KG completion.

Key facts. Cited by 83 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 May 2019.

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Citing papers per year: 2021: 18; 2022: 28; 2023: 12; 2024: 12; 2025: 8; 2026: 5.

83 papers.

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  1. 2021TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecastingcited by 67
  2. 2024Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Surveycited by 53
  3. 2024Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoningcited by 44
  4. 2022Knowledge Graph Embedding: A Survey from the Perspective of Representation Spacescited by 41
  5. 2021Boosting the Speed of Entity Alignment 10*: Dual Attention Matching Network with Normalized Hard Sample Miningcited by 37
  6. 2022SelfKG: Self-Supervised Entity Alignment in Knowledge Graphscited by 32
  7. 2021A Benchmark and Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learningcited by 31
  8. 2022Lifelong Embedding Learning and Transfer for Growing Knowledge Graphscited by 28
  9. 2021From Alignment to Assignment: Frustratingly Simple Unsupervised Entity Alignmentcited by 26
  10. 2021Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphscited by 25
  11. 2021Knowing the No-match: Entity Alignment with Dangling Casescited by 20
  12. 2022ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similaritiescited by 20
38 more
  1. 2021OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embeddingcited by 19
  2. 2021Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embeddingcited by 18
  3. 2022LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagationcited by 18
  4. 2024MKGL: Mastery of a Three-Word Languagecited by 17
  5. 2023A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignmentcited by 16
  6. 2022I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learningcited by 15
  7. 2021Bilinear Scoring Function Search for Knowledge Graph Learningcited by 11
  8. 2021Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustnesscited by 9
  9. 2022Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embeddingcited by 9
  10. 2022Informed Multi-context Entity Alignmentcited by 8
  11. 2023Revisit and Outstrip Entity Alignment: A Perspective of Generative Modelscited by 8
  12. 2024Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignmentcited by 8
  13. 2021Reinforcement Learning based Collective Entity Alignment with Adaptive Featurescited by 7
  14. 2021Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphscited by 7
  15. 2022Interactive Contrastive Learning for Self-supervised Entity Alignmentcited by 7
  16. 2022Ensemble Semi-supervised Entity Alignment via Cycle-teachingcited by 7
  17. 2022KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learningcited by 7
  18. 2023Deep Active Alignment of Knowledge Graph Entities and Schematacited by 7
  19. 2022Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entitiescited by 6
  20. 2022Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligencecited by 6
  21. 2023From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignmentcited by 6
  22. 2022Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignmentcited by 5
  23. 2023Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphscited by 5
  24. 2024Uncertainty Management in the Construction of Knowledge Graphs: a Surveycited by 5
  25. 2021Towards Entity Alignment in the Open World: An Unsupervised Approachcited by 4
  26. 2022Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Datacited by 4
  27. 2022μKG: A Library for Multi-source Knowledge Graph Embeddings and Applicationscited by 4
  28. 2023What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddingscited by 4
  29. 2023Improving Knowledge Graph Entity Alignment with Graph Augmentationcited by 3
  30. 2023Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systemscited by 3
  31. 2024Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Casescited by 3
  32. 2024Binder: Hierarchical Concept Representation through Order Embedding of Binary Vectorscited by 3
  33. 2021A Self-supervised Method for Entity Alignmentcited by 2
  34. 2022Jointly Learning Knowledge Embedding and Neighborhood Consensus with Relational Knowledge Distillation for Entity Alignmentcited by 2
  35. 2022Deep Reinforcement Learning for Entity Alignmentcited by 2
  36. 2022Guiding Neural Entity Alignment with Compatibilitycited by 2
  37. 2022Dependency-aware Self-training for Entity Alignmentcited by 2
  38. 2023Combating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignmentcited by 2

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