mlsanityData to 14 Oct 2026

Aligning Multiple Knowledge Graphs in a Single Pass

arXiv 2408.00662 ↗First posted 1 Aug 2024cs.CL cs.LGcited by 2

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Abstract (arXiv)

Entity alignment (EA) is to identify equivalent entities across different knowledge graphs (KGs), which can help fuse these KGs into a more comprehensive one. Previous EA methods mainly focus on aligning a pair of KGs, and to the best of our knowledge, no existing EA method considers aligning multiple (more than two) KGs. To fill this research gap, in this work, we study a novel problem of aligning multiple KGs and propose an effective framework named MultiEA to solve the problem. First, we embed the entities of all the candidate KGs into a common feature space by a shared KG encoder. Then, we explore three alignment strategies to minimize the distances among pre-aligned entities. In particular, we propose an innovative inference enhancement technique to improve the alignment performance by incorporating high-order similarities. Finally, to verify the effectiveness of MultiEA, we construct two new real-world benchmark datasets and conduct extensive experiments on them. The results show that our MultiEA can effectively and efficiently align multiple KGs in a single pass. We release the source codes of MultiEA at: https://github.com/kepsail/MultiEA.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 30 of its 63 references that are in the map. First posted on arXiv 1 Aug 2024.

Builds on

30 of 63 references.

References · 30

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  3. 2017Graph Attention Networkscited by 8,923
  4. 2019KGAT: Knowledge Graph Attention Network for Recommendationcited by 343
  5. 2016Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignmentcited by 128
  6. 2017Cross-lingual Entity Alignment via Joint Attribute-Preserving Embeddingcited by 127
  7. 2019Knowledge Graph Convolutional Networks for Recommender Systemscited by 121
  8. 2020A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphscited by 120
  9. 2019Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphscited by 106
  10. 2019Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregationcited by 101
  11. 2019Multi-Channel Graph Neural Network for Entity Alignmentcited by 86
  12. 2019Multi-view Knowledge Graph Embedding for Entity Alignmentcited by 74
18 more
  1. 2017Continuously Differentiable Exponential Linear Unitscited by 73
  2. 2020Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Frameworkcited by 70
  3. 2019Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Networkcited by 68
  4. 2015Modeling Relation Paths for Representation Learning of Knowledge Basescited by 56
  5. 2020Relational Reflection Entity Alignmentcited by 53
  6. 2020Interpretable and Efficient Heterogeneous Graph Convolutional Networkcited by 48
  7. 2019Aligning Cross-Lingual Entities with Multi-Aspect Informationcited by 46
  8. 2020Neighborhood Matching Network for Entity Alignmentcited by 44
  9. 2020TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphscited by 41
  10. 2019Jointly Learning Entity and Relation Representations for Entity Alignmentcited by 39
  11. 2022SelfKG: Self-Supervised Entity Alignment in Knowledge Graphscited by 32
  12. 2021LargeEA: Aligning Entities for Large-scale Knowledge Graphscited by 26
  13. 2023Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignmentcited by 24
  14. 2022LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagationcited by 18
  15. 2020Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learningcited by 16
  16. 2020Brain-inspired Search Engine Assistant based on Knowledge Graphcited by 13
  17. 2021Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustnesscited by 9
  18. 2023MultiEM: Efficient and Effective Unsupervised Multi-Table Entity Matchingcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Unsupervised Entity Alignment Based on Personalized Discriminative Rooted Treecited by 0
  2. 2026Graph Fusion Across Languages using Large Language Modelscited by 0