Link prediction on latent heterogeneous graphs
On graph data, the multitude of node or edge types gives rise to heterogeneous information networks (HINs). To preserve the heterogeneous semantics on HINs, the rich node/edge types become a cornerstone of HIN representation learning. However, in real-world scenarios, type information is often noisy...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2023
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/8190 https://ink.library.smu.edu.sg/context/sis_research/article/9193/viewcontent/3543507.3583284_pvoa_cc_by.pdf |
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| Institution: | Singapore Management University |
| Language: | English |