Corpus ID: 227229005

A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources

@article{Wang2020ASO,
  title={A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources},
  author={X. Wang and Deyu Bo and C. Shi and Shaohua Fan and Yanfang Ye and Philip S. Yu},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.14867}
}

X. Wang, Deyu Bo, +3 authors Philip S. Yu

Published 2020

Computer Science

ArXiv

Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension space while preserving the heterogeneous structures and semantics for downstream tasks (e.g., node/graph classification, node clustering, link prediction), has drawn considerable attentions in recent years. In this survey, we perform a comprehensive review of the recent development on HG… CONTINUE READING

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