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Knowledge Transfer for Out-of-Knowledge-Base Entities: A Graph Neural Network Approach

arXiv 1706.05674 ↗First posted 18 Jun 2017cs.CLcited by 102

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Abstract (arXiv)

Knowledge base completion (KBC) aims to predict missing information in a knowledge base.In this paper, we address the out-of-knowledge-base (OOKB) entity problem in KBC:how to answer queries concerning test entities not observed at training time. Existing embedding-based KBC models assume that all test entities are available at training time, making it unclear how to obtain embeddings for new entities without costly retraining. To solve the OOKB entity problem without retraining, we use graph neural networks (Graph-NNs) to compute the embeddings of OOKB entities, exploiting the limited auxiliary knowledge provided at test time.The experimental results show the effectiveness of our proposed model in the OOKB setting.Additionally, in the standard KBC setting in which OOKB entities are not involved, our model achieves state-of-the-art performance on the WordNet dataset. The code and dataset are available at https://github.com/takuo-h/GNN-for-OOKB

Key facts. Cited by 102 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jun 2017.

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Citing papers per year: 2020: 1; 2021: 27; 2022: 24; 2023: 24; 2024: 15; 2025: 6; 2026: 5.

102 papers.

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  1. 2020Permutation Invariant Graph Generation via Score-Based Generative Modelingcited by 263
  2. 2023Towards Foundation Models for Knowledge Graph Reasoningcited by 83
  3. 2021NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphscited by 71
  4. 2022GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networkscited by 57
  5. 2021BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessingcited by 50
  6. 2023InGram: Inductive Knowledge Graph Embedding via Relation Graphscited by 50
  7. 2021Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphscited by 47
  8. 2021OntoZSL: Ontology-enhanced Zero-shot Learningcited by 45
  9. 2022FMP: Toward Fair Graph Message Passing against Topology Biascited by 35
  10. 2023A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Materialcited by 34
  11. 2021Meta-Knowledge Transfer for Inductive Knowledge Graph Embeddingcited by 31
  12. 2022Relational Message Passing for Fully Inductive Knowledge Graph Completioncited by 29
38 more
  1. 2022Lifelong Embedding Learning and Transfer for Growing Knowledge Graphscited by 28
  2. 2021Inductive Relation Prediction by BERTcited by 27
  3. 2024A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoningcited by 25
  4. 2021Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Surveycited by 23
  5. 2025TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphscited by 23
  6. 2022Graph Neural Networks for Moleculescited by 21
  7. 2022Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphscited by 21
  8. 2024Towards Continual Knowledge Graph Embedding via Incremental Distillationcited by 17
  9. 2021Self-supervised Consensus Representation Learning for Attributed Graphcited by 15
  10. 2022Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Settingcited by 15
  11. 2023Generalizing to Unseen Elements: A Survey on Knowledge Extrapolation for Knowledge Graphscited by 14
  12. 2024Fast and Continual Knowledge Graph Embedding via Incremental LoRAcited by 14
  13. 2022Graph Neural Networks for Cross-Camera Data Associationcited by 13
  14. 2021Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidancecited by 12
  15. 2022RAILD: Towards Leveraging Relation Features for Inductive Link Prediction In Knowledge Graphscited by 12
  16. 2023Chasing Fairness in Graphs: A GNN Architecture Perspectivecited by 12
  17. 2022Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approachcited by 8
  18. 2022Facing Changes: Continual Entity Alignment for Growing Knowledge Graphscited by 8
  19. 2022Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Informationcited by 8
  20. 2023Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?cited by 8
  21. 2021Generalized Equivariance and Preferential Labeling for GNN Node Classificationcited by 7
  22. 2022Disconnected Emerging Knowledge Graph Oriented Inductive Link Predictioncited by 7
  23. 2023Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graphcited by 7
  24. 2023Fairness-aware Message Passing for Graph Neural Networkscited by 7
  25. 2024A Self-Explainable Heterogeneous GNN for Relational Deep Learningcited by 7
  26. 2021Benchmarking Knowledge-driven Zero-shot Learningcited by 6
  27. 2021Survey on English Entity Linking on Wikidatacited by 6
  28. 2022Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entitiescited by 6
  29. 2021Dense Graph Convolutional Neural Networks on 3D Meshes for 3D Object Segmentation and Classificationcited by 4
  30. 2021Computing Steiner Trees using Graph Neural Networkscited by 4
  31. 2023Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approachcited by 4
  32. 2023Higher-Order Expander Graph Propagationcited by 4
  33. 2024Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learningcited by 4
  34. 2024GATE: How to Keep Out Intrusive Neighborscited by 4
  35. 2021Explicit Pairwise Factorized Graph Neural Network for Semi-Supervised Node Classificationcited by 3
  36. 2022Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifierscited by 3
  37. 2023Towards Semantically Enriched Embeddings for Knowledge Graph Completioncited by 3
  38. 2024CrysToGraph: A Comprehensive Predictive Model for Crystal Materials Properties and the Benchmarkcited by 3

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