Predicting Influence Probabilities using Graph Convolutional Networks.
Jing LiuYudi ChenDuanshun LiNoseong ParkKisung LeeDongwon LeePublished in: IEEE BigData (2019)
Keyphrases
- highly connected
- average degree
- fully connected
- random walk
- small world
- graph theory
- graph representation
- community discovery
- directed graph
- graph structure
- graph structures
- social influence
- graph model
- weighted graph
- probability distribution
- information diffusion
- directed edges
- edge weights
- graph theoretic
- degree distribution
- social networks
- network analysis
- structured data
- conditional probabilities
- complex networks
- connected components
- dynamic networks
- bayesian networks
- semi supervised
- social graphs
- overlapping communities
- structural patterns
- citation networks
- graph partitioning
- network size
- sparse coding
- deep learning
- graph matching
- bipartite graph
- directed acyclic graph