43 citations · 45 across the 2 of their papers we have counts for
3 papers
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
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…
cs.LG2017★ 43 cited
Active Learning for Graph Embedding
Hongyun Cai, Vincent W. Zheng, Kevin Chen-Chuan Chang
Graph embedding provides an efficient solution for graph analysis by converting the graph into a low-dimensional space which preserves the structure information. In contrast to the…