MM-HGNN: Multimodal Representation Learning Heterogeneous Graph Neural Network
Abstract Multimodal learning heterogeneous graphs are very challenging because of the diverse structures and data modalities. The existing graph neural networks cannot efficiently capture both the multimodality of the data and the inherent heterogeneity of such graphs. In this paper, we propose Mult...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00820-9 |
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