mlsanityData to 14 Oct 2026

Graph Learning based Recommender Systems: A Review

arXiv 2105.06339 ↗First posted 13 May 2021cs.IR cs.AI cs.LGcited by 59

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Abstract (arXiv)

Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS). GLRS employ advanced graph learning approaches to model users' preferences and intentions as well as items' characteristics for recommendations. Differently from other RS approaches, including content-based filtering and collaborative filtering, GLRS are built on graphs where the important objects, e.g., users, items, and attributes, are either explicitly or implicitly connected. With the rapid development of graph learning techniques, exploring and exploiting homogeneous or heterogeneous relations in graphs are a promising direction for building more effective RS. In this paper, we provide a systematic review of GLRS, by discussing how they extract important knowledge from graph-based representations to improve the accuracy, reliability and explainability of the recommendations. First, we characterize and formalize GLRS, and then summarize and categorize the key challenges and main progress in this novel research area. Finally, we share some new research directions in this vibrant area.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Builds on 34 of its 80 references that are in the map. First posted on arXiv 13 May 2021.

Builds on

34 of 80 references.

References · 34

  1. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
  2. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,919
  3. 2020LightGCN: Simplifying and Powering Graph Convolution Network for Recommendationcited by 1,139
  4. 2018Graph Convolutional Neural Networks for Web-Scale Recommender Systemscited by 1,138
  5. 2019Graph Neural Networks for Social Recommendationcited by 714
  6. 2020Graph Neural Networks in Recommender Systems: A Surveycited by 494
  7. 2019KGAT: Knowledge Graph Attention Network for Recommendationcited by 343
  8. 2018Session-based Recommendation with Graph Neural Networkscited by 312
  9. 2018Explainable Recommendation: A Survey and New Perspectivescited by 210
  10. 2020A Survey on Knowledge Graph-Based Recommender Systemscited by 170
  11. 2018RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systemscited by 138
  12. 2017Heterogeneous Information Network Embedding for Recommendationcited by 133
22 more
  1. 2019Sequential Recommender Systems: Challenges, Progress and Prospectscited by 115
  2. 2019Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systemscited by 107
  3. 2019A Survey on Session-based Recommender Systemscited by 97
  4. 2019Representation Learning for Attributed Multiplex Heterogeneous Networkcited by 91
  5. 2017Geometric Matrix Completion with Recurrent Multi-Graph Neural Networkscited by 88
  6. 2019Inductive Matrix Completion Based on Graph Neural Networkscited by 86
  7. 2019Session-based Social Recommendation via Dynamic Graph Attention Networkscited by 76
  8. 2021Cross-Domain Recommendation: Challenges, Progress, and Prospectscited by 74
  9. 2019Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendationcited by 71
  10. 2019A Neural Influence Diffusion Model for Social Recommendationcited by 70
  11. 2018Improving Question Answering by Commonsense-Based Pre-Trainingcited by 66
  12. 2018Sequence-Aware Recommender Systemscited by 58
  13. 2019STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systemscited by 54
  14. 2019Memory Augmented Graph Neural Networks for Sequential Recommendationcited by 46
  15. 2020DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendationcited by 46
  16. 2019Rethinking the Item Order in Session-based Recommendation with Graph Neural Networkscited by 43
  17. 2020Graph Convolutional Network for Recommendation with Low-pass Collaborative Filterscited by 32
  18. 2019Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networkscited by 26
  19. 2020Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Predictioncited by 21
  20. 2020Deep Learning on Knowledge Graph for Recommender System: A Surveycited by 19
  21. 2019Collaborative Similarity Embedding for Recommender Systemscited by 13
  22. 2019Binarized Collaborative Filtering with Distilling Graph Convolutional Networkscited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 6; 2022: 13; 2023: 10; 2024: 11; 2025: 13; 2026: 6.

59 papers.

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  1. 2022A Survey of Graph Neural Networks for Social Recommender Systemscited by 65
  2. 2022Graph Condensation via Receptive Field Distribution Matchingcited by 60
  3. 2022Survey on Graph Neural Network Acceleration: An Algorithmic Perspectivecited by 26
  4. 2023A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applicationscited by 22
  5. 2021A Semi-Personalized System for User Cold Start Recommendation on Music Streaming Appscited by 21
  6. 2021Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networkscited by 19
  7. 2022COIN: Co-Cluster Infomax for Bipartite Graphscited by 14
  8. 2024Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directionscited by 13
  9. 2021Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoderscited by 12
  10. 2023STERLING: Synergistic Representation Learning on Bipartite Graphscited by 12
  11. 2024Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendationcited by 11
  12. 2022Graph-Time Convolutional Neural Networks: Architecture and Theoretical Analysiscited by 10
38 more
  1. 2023A Survey of Graph Prompting Methods: Techniques, Applications, and Challengescited by 10
  2. 2023Privacy-Preserving Graph Machine Learning from Data to Computation: A Surveycited by 10
  3. 2024Disentangled Condensation for Large-scale Graphscited by 10
  4. 2022Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunitiescited by 9
  5. 2021Recommender systems based on graph embedding techniques: A comprehensive reviewcited by 8
  6. 2024Async Learned User Embeddings for Ads Delivery Optimizationcited by 7
  7. 2022Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendationcited by 6
  8. 2024Modeling Temporal Positive and Negative Excitation for Sequential Recommendationcited by 6
  9. 2024Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Predictioncited by 5
  10. 2024Model Selection with Model Zoo via Graph Learningcited by 5
  11. 2022Ranking-based Group Identification via Factorized Attention on Social Tripartite Graphcited by 4
  12. 2023Graph-based Alignment and Uniformity for Recommendationcited by 4
  13. 2023Unified Pretraining for Recommendation via Task Hypergraphscited by 4
  14. 2025Graph Foundation Models for Recommendation: A Comprehensive Surveycited by 4
  15. 2021Aspect-driven User Preference and News Representation Learning for News Recommendationcited by 3
  16. 2025A Comprehensive Review on Harnessing Large Language Models to Overcome Recommender System Challengescited by 3
  17. 2025AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agentscited by 3
  18. 2022Physics-Informed Graph Learningcited by 2
  19. 2022Modeling Multi-interest News Sequence for News Recommendationcited by 2
  20. 2023Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluationcited by 2
  21. 2023OSP: Boosting Distributed Model Training with 2-stage Synchronizationcited by 2
  22. 2023Everything Perturbed All at Once: Enabling Differentiable Graph Attackscited by 2
  23. 2024EDGE-Rec: Efficient and Data-Guided Edge Diffusion For Recommender Systems Graphscited by 2
  24. 2022A Bird's-Eye Tutorial of Graph Attention Architecturescited by 1
  25. 2024Personalized Negative Reservoir for Incremental Learning in Recommender Systemscited by 1
  26. 2024Review of Explainable Graph-Based Recommender Systemscited by 1
  27. 2025AMPLE: Event-Driven Accelerator for Mixed-Precision Inference of Graph Neural Networkscited by 1
  28. 2025Dynamic Mixture-of-Experts for Incremental Graph Learningcited by 1
  29. 2025RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendationcited by 1
  30. 2025Multitask Learning with Learned Task Relationshipscited by 1
  31. 2026InfGraND: An Influence-Guided GNN-to-MLP Knowledge Distillationcited by 1
  32. 2021Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborationscited by 0
  33. 2022Modeling Complex Dependencies for Session-based Recommendations via Graph Neural Networkscited by 0
  34. 2022Efficient Graph based Recommender System with Weighted Averaging of Messagescited by 0
  35. 2023A Comparative Analysis of Bias Amplification in Graph Neural Network Approaches for Recommender Systemscited by 0
  36. 2024GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstructioncited by 0
  37. 2025Towards Responsible AI in Education: Hybrid Recommendation System for K-12 Students Case Studycited by 0
  38. 2025Heterogeneous Graph Backdoor Attackcited by 0

50 most cited of 59 All 59 (JSON)