mlsanityData to 7 Oct 2026

Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces

arXiv 2211.03536 ↗First posted 7 Nov 2022cs.LG cs.AI cs.CLcited by 41

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Abstract (arXiv)

Knowledge graph embedding (KGE) is an increasingly popular technique that aims to represent entities and relations of knowledge graphs into low-dimensional semantic spaces for a wide spectrum of applications such as link prediction, knowledge reasoning and knowledge completion. In this paper, we provide a systematic review of existing KGE techniques based on representation spaces. Particularly, we build a fine-grained classification to categorise the models based on three mathematical perspectives of the representation spaces: (1) Algebraic perspective, (2) Geometric perspective, and (3) Analytical perspective. We introduce the rigorous definitions of fundamental mathematical spaces before diving into KGE models and their mathematical properties. We further discuss different KGE methods over the three categories, as well as summarise how spatial advantages work over different embedding needs. By collating the experimental results from downstream tasks, we also explore the advantages of mathematical space in different scenarios and the reasons behind them. We further state some promising research directions from a representation space perspective, with which we hope to inspire researchers to design their KGE models as well as their related applications with more consideration of their mathematical space properties.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). Builds on 107 of its 243 references that are in the map. First posted on arXiv 7 Nov 2022.

Builds on

107 of 243 references.

References · 107

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38 more
  1. 2019How Can We Know What Language Models Know?cited by 953
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  4. 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 893
  5. 2017Convolutional 2D Knowledge Graph Embeddingscited by 729
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50 most cited of 107 All 107 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 13; 2025: 14; 2026: 9.

41 papers.

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  1. 2023A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challengecited by 55
  2. 2023Knowledge Graph Embedding: An Overviewcited by 10
  3. 2024BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Drivingcited by 10
  4. 2025HypKG: Hypergraph-based Knowledge Graph Contextualization for Precision Healthcarecited by 9
  5. 2025Automated Knowledge Graph Construction using Large Language Models and Sentence Complexity Modellingcited by 9
  6. 2024Large Language Model Enhanced Knowledge Representation Learning: A Surveycited by 6
  7. 2025Rethinking Regularization Methods for Knowledge Graph Completioncited by 6
  8. 2023Clinical Trial Recommendations Using Semantics-Based Inductive Inference and Knowledge Graph Embeddingscited by 4
  9. 2024Investigating Representation Universality: Case Study on Genealogical Representationscited by 4
  10. 2025A Survey of Link Prediction in N-ary Knowledge Graphscited by 4
  11. 2024Cardinality Estimation on Hyper-relational Knowledge Graphscited by 3
  12. 2024HRGraph: Leveraging LLMs for HR Data Knowledge Graphs with Information Propagation-based Job Recommendationcited by 3
29 more
  1. 2025Large Language Models for Knowledge Graph Embedding: A Surveycited by 3
  2. 2025Can We Edit LLMs for Long-Tail Biomedical Knowledge?cited by 3
  3. 2024CiteFusion: An Ensemble Framework for Citation Intent Classification Harnessing Dual-Model Binary Couples and SHAP Analysescited by 2
  4. 2024Knowledge Graph Embeddings: A Comprehensive Survey on Capturing Relation Propertiescited by 2
  5. 2024Aligning Generalisation Between Humans and Machinescited by 2
  6. 2023Knowledge Graphs are not Created Equal: Exploring the Properties and Structure of Real KGscited by 1
  7. 2024Context-aware knowledge graph framework for traffic speed forecasting using graph neural networkcited by 1
  8. 2024Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learningcited by 1
  9. 2025Diffusion-based Hierarchical Negative Sampling for Multimodal Knowledge Graph Completioncited by 1
  10. 2025A Systematic Evaluation of Knowledge Graph Embeddings for Gene-Disease Association Predictioncited by 1
  11. 2025Two-dimensional Taxonomy for N-ary Knowledge Representation Learning Methodscited by 1
  12. 2025Flow-Modulated Scoring for Semantic-Aware Knowledge Graph Completioncited by 1
  13. 2023Learning with Geometry: Including Riemannian Geometric Features in Coefficient of Pressure Prediction on Aircraft Wingscited by 0
  14. 2024DELE: Deductive EL++ Embeddings for Knowledge Base Completioncited by 0
  15. 2024Domain and Range Aware Synthetic Negatives Generation for Knowledge Graph Embedding Modelscited by 0
  16. 2024A Decade of Deep Learning: A Survey on The Magnificent Sevencited by 0
  17. 2025FAIRTOPIA: Envisioning Multi-Agent Guardianship for Disrupting Unfair AI Pipelinescited by 0
  18. 2025Bio-KGvec2go: Serving up-to-date Dynamic Biomedical Knowledge Graph Embeddingscited by 0
  19. 2025Approximate Diverse k-nearest Neighbor Search in Vector Databasecited by 0
  20. 2025HyperComplEx: Adaptive Multi-Space Knowledge Graph Embeddingscited by 0
  21. 2026LEC-KG: An LLM-Embedding Collaborative Framework for Domain-Specific Knowledge Graph Construction -- A Case Study on SDGscited by 0
  22. 2026Relations Are Channels: Knowledge Graph Embedding via Kraus Decompositionscited by 0
  23. 2026FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanismcited by 0
  24. 2026Enhancing Protein Representation Learning via Manifold Restore Mixingcited by 0
  25. 2026Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Surveycited by 0
  26. 2026Relation Geometry in Semantic Space of Language Modelscited by 0
  27. 2026SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoningcited by 0
  28. 2026More Perspectives, Stronger Signals: Multi-Perspective Enhancement and Progressive Fusion for Multimodal Entity Representation Learningcited by 0
  29. 2026ImbalancE: Inference-Time Latent Search Against Degree Imbalance in Link Predictioncited by 0