16 citations · 59 across the 13 of their papers we have counts for
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cs.AI2019★ 2 cited
Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding
Wenqiang Liu, Hongyun Cai, Xu Cheng +3
The goal of representation learning of knowledge graph is to encode both entities and relations into a low-dimensional embedding spaces. Many recent works have demonstrated the ben…
cs.SI2019★ 4 cited
Initialization for Network Embedding: A Graph Partition Approach
Wenqing Lin, Feng He, Faqiang Zhang +2
Network embedding has been intensively studied in the literature and widely used in various applications, such as link prediction and node classification. While previous work focus…