Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey

Abstract

Graph Neural Networks (GNNs) have emerged as a powerful paradigm in Knowledge Graphs (KGs) due to their intrinsic ability to model graph-structured data. However, there remains a lack of a systematic review about GNN-based methodologies across the entire knowledge graph technologies pipeline. To address this gap, we first propose a novel two-level taxonomy framework for GNN-based knowledge graph technologies: the KG technologies pipeline and GNN-based perspective. Specifically, the knowledge graph technologies pipeline covers knowledge graph construction, knowledge graph embedding, knowledge reasoning and knowledge graph applications. Meanwhile, the GNN-based perspective provides a new categorization of knowledge graph technologies with GNN models, such as GCN, GAT, and HGNN. Then, we analyze the advantages of GNN technology based on the characteristics of different tasks in the knowledge graph lifecycle. Furthermore, we detailed review various GNN-based models for knowledge graph following the proposed taxonomy, and summarize strengths and limitations. Finally, we discuss unresolved challenges and outline promising directions for future research.

Recently Accepted for publication in ACM Computing Surveys. This is the accepted manuscript version, and the final published version available at ACM Computing Surveys:https://doi.org/10.1145/3814608. Paper list at Github: https://github.com/sunxiaobei/awesome-gnn-based-knowledge-graphs

References in corpus (20)

• A Comprehensive Survey on Graph Neural Networks
• Knowledge Graphs
• Unifying Large Language Models and Knowledge Graphs: A Roadmap
• Knowledge Graph Convolutional Networks for Recommender Systems
• Learning Intents behind Interactions with Knowledge Graph for Recommendation
• Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs
• Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction
• SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization
• ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation
• Temporal Knowledge Graph Completion: A Survey
• EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs
• DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network
• Toward Subgraph-Guided Knowledge Graph Question Generation with Graph Neural Networks
• Complex Temporal Question Answering on Knowledge Graphs
• Graph Foundation Models: Concepts, Opportunities and Challenges
• Computational Politeness in Natural Language Processing: A Survey
• Learning Multi-graph Structure for Temporal Knowledge Graph Reasoning
• Complex Factoid Question Answering with a Free-Text Knowledge Graph
• A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective
• GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning