mlsanityData to 7 Oct 2026

Knowledge Graph Reasoning with Logics and Embeddings: Survey and Perspective

arXiv 2202.07412 ↗First posted 15 Feb 2022cs.AIcited by 18

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Abstract (arXiv)

Knowledge graph (KG) reasoning is becoming increasingly popular in both academia and industry. Conventional KG reasoning based on symbolic logic is deterministic, with reasoning results being explainable, while modern embedding-based reasoning can deal with uncertainty and predict plausible knowledge, often with high efficiency via vector computation. A promising direction is to integrate both logic-based and embedding-based methods, with the vision to have advantages of both. It has attracted wide research attention with more and more works published in recent years. In this paper, we comprehensively survey these works, focusing on how logics and embeddings are integrated. We first briefly introduce preliminaries, then systematically categorize and discuss works of logic and embedding-aware KG reasoning from different perspectives, and finally conclude and discuss the challenges and further directions.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 26 of its 74 references that are in the map. First posted on arXiv 15 Feb 2022.

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26 of 74 references.

References · 26

  1. 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 929
  2. 2016Complex Embeddings for Simple Link Predictioncited by 897
  3. 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 893
  4. 2019DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphscited by 173
  5. 2020Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddingscited by 169
  6. 2017End-to-End Differentiable Provingcited by 159
  7. 2019Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Predictioncited by 133
  8. 2020Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphscited by 128
  9. 2018Embedding Logical Queries on Knowledge Graphscited by 120
  10. 2020Complex Query Answering with Neural Link Predictorscited by 98
  11. 2021ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphscited by 78
  12. 2019Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoningcited by 63
14 more
  1. 2020Learning Reasoning Strategies in End-to-End Differentiable Provingcited by 60
  2. 2015Modeling Relation Paths for Representation Learning of Knowledge Basescited by 56
  3. 2015Traversing Knowledge Graphs in Vector Spacecited by 51
  4. 2017Knowledge Graph Embedding with Iterative Guidance from Soft Rulescited by 51
  5. 2021OntoZSL: Ontology-enhanced Zero-shot Learningcited by 45
  6. 2018Improving Knowledge Graph Embedding Using Simple Constraintscited by 36
  7. 2019Differentiable Reasoning on Large Knowledge Bases and Natural Languagecited by 30
  8. 2020Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoderscited by 28
  9. 2019Rule-Guided Compositional Representation Learning on Knowledge Graphscited by 16
  10. 2021Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embeddingcited by 15
  11. 2021Billion-scale Pre-trained E-commerce Product Knowledge Graph Modelcited by 13
  12. 2021Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graphcited by 9
  13. 2013Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logiccited by 7
  14. 2020IterefinE: Iterative KG Refinement Embeddings using Symbolic Knowledgecited by 3

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Citing papers per year: 2022: 2; 2023: 9; 2024: 2; 2025: 5.

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  1. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  2. 2023Large Language Models and Knowledge Graphs: Opportunities and Challengescited by 71
  3. 2023Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databasescited by 35
  4. 2023Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generationcited by 19
  5. 2023Large Knowledge Model: Perspectives and Challengescited by 12
  6. 2024Ontology Embedding: A Survey of Methods, Applications and Resourcescited by 12
  7. 2025Automated Knowledge Graph Construction using Large Language Models and Sentence Complexity Modellingcited by 9
  8. 2022Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligencecited by 5
  9. 2023Knowledge Graphs Queryingcited by 5
  10. 2023ReOnto: A Neuro-Symbolic Approach for Biomedical Relation Extractioncited by 4
  11. 2025Long-Form Information Alignment Evaluation Beyond Atomic Factscited by 4
  12. 2023A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learningcited by 3
6 more
  1. 2024Untargeted Adversarial Attack on Knowledge Graph Embeddingscited by 3
  2. 2025Large Language Model-Enhanced Symbolic Reasoning for Knowledge Base Completioncited by 2
  3. 2023Neuro-Symbolic RDF and Description Logic Reasoners: The State-Of-The-Art and Challengescited by 1
  4. 2025Ontology-Enhanced Knowledge Graph Completion using Large Language Modelscited by 1
  5. 2023Logic Diffusion for Knowledge Graph Reasoningcited by 0
  6. 2025A Survey of Task-Oriented Knowledge Graph Reasoning: Status, Applications, and Prospectscited by 0