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Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

arXiv 1905.11605 ↗First posted 28 May 2019cs.LG cs.CLcited by 68

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Abstract (arXiv)

Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs. In this paper, we introduce the topic entity graph, a local sub-graph of an entity, to represent entities with their contextual information in KG. From this view, the KB-alignment task can be formulated as a graph matching problem; and we further propose a graph-attention based solution, which first matches all entities in two topic entity graphs, and then jointly model the local matching information to derive a graph-level matching vector. Experiments show that our model outperforms previous state-of-the-art methods by a large margin.

Key facts. Cited by 68 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 May 2019.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 17; 2022: 21; 2023: 12; 2024: 12; 2025: 5; 2026: 1.

68 papers.

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  1. 2023Knowledge Graphs: Opportunities and Challengescited by 70
  2. 2021Search to aggregate neighborhood for graph neural networkcited by 48
  3. 2022Multi-modal Contrastive Representation Learning for Entity Alignmentcited by 38
  4. 2021Boosting the Speed of Entity Alignment 10*: Dual Attention Matching Network with Normalized Hard Sample Miningcited by 37
  5. 2022SelfKG: Self-Supervised Entity Alignment in Knowledge Graphscited by 32
  6. 2021A Benchmark and Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learningcited by 31
  7. 2022MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybridcited by 30
  8. 2021From Alignment to Assignment: Frustratingly Simple Unsupervised Entity Alignmentcited by 26
  9. 2022Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferabilitycited by 26
  10. 2023Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Typescited by 21
  11. 2021WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Datasetcited by 20
  12. 2021The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphscited by 19
38 more
  1. 2022LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagationcited by 18
  2. 2023A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignmentcited by 16
  3. 2024KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledgecited by 16
  4. 2024Towards Principled Graph Transformerscited by 11
  5. 2021Stochastic Iterative Graph Matchingcited by 10
  6. 2022TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Naturecited by 10
  7. 2025PLANETALIGN: A Comprehensive Python Library for Benchmarking Network Alignmentcited by 10
  8. 2021Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustnesscited by 9
  9. 2022Informed Multi-context Entity Alignmentcited by 8
  10. 2024Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignmentcited by 8
  11. 2021Reinforcement Learning based Collective Entity Alignment with Adaptive Featurescited by 7
  12. 2022Interactive Contrastive Learning for Self-supervised Entity Alignmentcited by 7
  13. 2022An Accurate Unsupervised Method for Joint Entity Alignment and Dangling Entity Detectioncited by 7
  14. 2022Ensemble Semi-supervised Entity Alignment via Cycle-teachingcited by 7
  15. 2023AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Modelscited by 7
  16. 2023SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detectioncited by 7
  17. 2021Optimizing Sparse Matrix Multiplications for Graph Neural Networkscited by 6
  18. 2023State of the Art and Potentialities of Graph-level Learningcited by 6
  19. 2024Large language models as oracles for instantiating ontologies with domain-specific knowledgecited by 6
  20. 2024Representation Learning for Frequent Subgraph Miningcited by 5
  21. 2024Uncertainty Management in the Construction of Knowledge Graphs: a Surveycited by 5
  22. 2021Towards Entity Alignment in the Open World: An Unsupervised Approachcited by 4
  23. 2021Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answeringcited by 4
  24. 2022Neural Graph Matching for Pre-training Graph Neural Networkscited by 4
  25. 2022Dangling-Aware Entity Alignment with Mixed High-Order Proximitiescited by 4
  26. 2022BiFeat: Supercharge GNN Training via Graph Feature Quantizationcited by 4
  27. 2024Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Casescited by 3
  28. 2021A Self-supervised Method for Entity Alignmentcited by 2
  29. 2022Jointly Learning Knowledge Embedding and Neighborhood Consensus with Relational Knowledge Distillation for Entity Alignmentcited by 2
  30. 2022Semi-constraint Optimal Transport for Entity Alignment with Dangling Casescited by 2
  31. 2022Privacy-Preserved Neural Graph Similarity Learningcited by 2
  32. 2023Shape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysiscited by 2
  33. 2023i-Align: an interpretable knowledge graph alignment modelcited by 2
  34. 2024Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decodingcited by 2
  35. 2024Aligning Multiple Knowledge Graphs in a Single Passcited by 2
  36. 2021Cross-lingual Entity Alignment with Adversarial Kernel Embedding and Adversarial Knowledge Translationcited by 1
  37. 2022Entity Alignment For Knowledge Graphs: Progress, Challenges, and Empirical Studiescited by 1
  38. 2022Exploiting Global Semantic Similarities in Knowledge Graphs by Relational Prototype Entitiescited by 1

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