ImGAGN: Imbalanced Network Embedding via Generative Adversarial Graph Networks.
Liang QuHuaisheng ZhuRuiqi ZhengYuhui ShiHongzhi YinPublished in: KDD (2021)
Keyphrases
- network structure
- complex networks
- sparsely connected
- network size
- dynamic networks
- highly connected
- computer networks
- average degree
- fully connected
- small world
- protein interaction networks
- network topologies
- network model
- citation networks
- network design
- degree distribution
- network parameters
- link formation
- social networks
- counter propagation
- overlapping communities
- clustering coefficient
- scale free
- community discovery
- transport network
- real world networks
- small world networks
- community structure
- heterogeneous networks
- real world social networks
- network resources
- random graphs
- social network analysis
- network evolution
- path length
- edge weights
- functional modules
- densely connected
- directed edges
- network traffic
- connectionist networks
- network properties
- wireless sensor networks
- heterogeneous social networks
- internet traffic
- graph embedding
- peer to peer
- telecommunication networks
- graphical representation
- biological networks
- graph theory
- random graph models
- directed graph
- communication networks
- link prediction
- spanning tree
- power law
- access points
- optical networks
- information networks
- network nodes