10.1k citations · 12.1k across the 55 of their papers we have counts for
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Search Efficient Binary Network Embedding
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Traditional network embedding primarily focuses on learning a continuous vector representation for each node, preserving network structure and/or node content information, such tha…
Attributed Network Embedding via Subspace Discovery
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Network embedding aims to learn a latent, low-dimensional vector representations of network nodes, effective in supporting various network analytic tasks. While prior arts on netwo…
SINE: Scalable Incomplete Network Embedding
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Attributed network embedding aims to learn low-dimensional vector representations for nodes in a network, where each node contains rich attributes/features describing node content.…
MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Network embedding in heterogeneous information networks (HINs) is a challenging task, due to complications of different node types and rich relationships between nodes. As a result…
Network Representation Learning: A Survey
Daokun Zhang, Jie Yin, Xingquan Zhu +1
With the widespread use of information technologies, information networks are becoming increasingly popular to capture complex relationships across various disciplines, such as soc…