mlsanityData to 7 Oct 2026

Multiplex Heterogeneous Graph Convolutional Network

arXiv 2208.06129 ↗First posted 12 Aug 2022cs.SI cs.AI cs.LGcited by 27

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Abstract (arXiv)

Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous network data, ranging from link prediction to node classification. However, most existing works ignore the relation heterogeneity with multiplex network between multi-typed nodes and different importance of relations in meta-paths for node embedding, which can hardly capture the heterogeneous structure signals across different relations. To tackle this challenge, this work proposes a Multiplex Heterogeneous Graph Convolutional Network (MHGCN) for heterogeneous network embedding. Our MHGCN can automatically learn the useful heterogeneous meta-path interactions of different lengths in multiplex heterogeneous networks through multi-layer convolution aggregation. Additionally, we effectively integrate both multi-relation structural signals and attribute semantics into the learned node embeddings with both unsupervised and semi-supervised learning paradigms. Extensive experiments on five real-world datasets with various network analytical tasks demonstrate the significant superiority of MHGCN against state-of-the-art embedding baselines in terms of all evaluation metrics.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Builds on 32 of its 46 references that are in the map. First posted on arXiv 12 Aug 2022.

Builds on

32 of 46 references.

References · 32

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2017Graph Attention Networkscited by 8,854
  3. 2017Inductive Representation Learning on Large Graphscited by 6,284
  4. 2016node2vec: Scalable Feature Learning for Networkscited by 1,913
  5. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  6. 2014DeepWalk: Online Learning of Social Representationscited by 1,543
  7. 2019Simplifying Graph Convolutional Networkscited by 1,470
  8. 2020LightGCN: Simplifying and Powering Graph Convolution Network for Recommendationcited by 1,134
  9. 2019Heterogeneous Graph Attention Networkcited by 732
  10. 2015LINE: Large-scale Information Network Embeddingcited by 582
  11. 2020Heterogeneous Graph Transformercited by 581
  12. 2019Graph Transformer Networkscited by 520
20 more
  1. 2020MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embeddingcited by 304
  2. 2017Heterogeneous Information Network Embedding for Recommendationcited by 133
  3. 2020AM-GCN: Adaptive Multi-channel Graph Convolutional Networkscited by 121
  4. 2019Unsupervised Attributed Multiplex Network Embeddingcited by 95
  5. 2019Representation Learning for Attributed Multiplex Heterogeneous Networkcited by 91
  6. 2021HDMI: High-order Deep Multiplex Infomaxcited by 82
  7. 2021Knowledge-aware Coupled Graph Neural Network for Social Recommendationcited by 49
  8. 2019NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorizationcited by 48
  9. 2021Graph Meta Network for Multi-Behavior Recommendationcited by 38
  10. 2022Contrastive Meta Learning with Behavior Multiplicity for Recommendationcited by 37
  11. 2020Scalable Graph Neural Networks for Heterogeneous Graphscited by 31
  12. 2019Fast and Accurate Network Embeddings via Very Sparse Random Projectioncited by 29
  13. 2021Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Networkcited by 28
  14. 2018Billion-scale Network Embedding with Iterative Random Projectioncited by 25
  15. 2017Principled Multilayer Network Embeddingcited by 24
  16. 2019Relation Structure-Aware Heterogeneous Information Network Embeddingcited by 19
  17. 2021Social Recommendation with Self-Supervised Metagraph Informax Networkcited by 18
  18. 2021Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networkscited by 13
  19. 2021Recent Advances in Heterogeneous Relation Learning for Recommendationcited by 13
  20. 2021Click-Through Rate Prediction with Multi-Modal Hypergraphscited by 12

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 6; 2024: 10; 2025: 7; 2026: 2.

27 papers.

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  1. 2024HiGPT: Heterogeneous Graph Language Modelcited by 44
  2. 2023Homophily-oriented Heterogeneous Graph Rewiringcited by 18
  3. 2022Convolutional Learning on Multigraphscited by 10
  4. 2023Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomialscited by 8
  5. 2025Cooperation of Experts: Fusing Heterogeneous Information with Large Margincited by 6
  6. 2022Learning with Multigraph Convolutional Filterscited by 5
  7. 2024Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modelingcited by 5
  8. 2024Dual-Channel Multiplex Graph Neural Networks for Recommendationcited by 5
  9. 2023Bridging Trustworthiness and Open-World Learning: An Exploratory Neural Approach for Enhancing Interpretability, Generalization, and Robustnesscited by 4
  10. 2023Attributed Multi-order Graph Convolutional Network for Heterogeneous Graphscited by 2
  11. 2024UMGAD: Unsupervised Multiplex Graph Anomaly Detectioncited by 2
  12. 2025ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusioncited by 2
15 more
  1. 2025Simple and Efficient Heterogeneous Temporal Graph Neural Networkcited by 2
  2. 2023Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributescited by 1
  3. 2024HGTDR: Advancing Drug Repurposing with Heterogeneous Graph Transformerscited by 1
  4. 2024Multi-Channel Hypergraph Contrastive Learning for Matrix Completioncited by 1
  5. 2026Modality as Heterogeneity: Node Splitting and Graph Rewiring for Multimodal Graph Learningcited by 1
  6. 2023Random Walk on Multiple Networkscited by 0
  7. 2024Generative-Contrastive Heterogeneous Graph Neural Networkcited by 0
  8. 2024Disentangled Hyperbolic Representation Learning for Heterogeneous Graphscited by 0
  9. 2024LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphscited by 0
  10. 2024Perturbation Ontology based Graph Attention Networkscited by 0
  11. 2025EdgeGFL: Rethinking Edge Information in Graph Feature Preference Learningcited by 0
  12. 2025Corporate Fraud Detection in Rich-yet-Noisy Financial Graphcited by 0
  13. 2025Incorporating Attributes and Multi-Scale Structures for Heterogeneous Graph Contrastive Learningcited by 0
  14. 2025Are Heterogeneous Graph Neural Networks Truly Effective for Node Classification? A Causal Perspectivecited by 0
  15. 2026Mapping Text to Multiplex Graph: Prompt Compression as L'evy Walk-Guided Graph Pruningcited by 0