Learning Temporal Interaction Graph Embedding via Coupled Memory Networks

Zhen Zhang
Zhen Zhang
Jianfeng Zhang
Jianfeng Zhang
Chengwei Yao
Chengwei Yao
Zhao Li
Zhao Li

WWW '20: The Web Conference 2020 Taipei Taiwan April, 2020, pp. 3049-3055, 2020.

Cited by: 0|Bibtex|Views104|DOI:https://doi.org/10.1145/3366423.3380076
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Other Links: dl.acm.org|academic.microsoft.com|dblp.uni-trier.de

Abstract:

Graph embedding has become the research focus in both academic and industrial communities due to its powerful capabilities. The majority of existing work overwhelmingly learn node embeddings in the context of static, plain or attributed, homogeneous graphs. However, many real-world applications frequently involve bipartite graphs with tem...More

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