GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks.
Tianxiang ZhaoXiang ZhangSuhang WangPublished in: WSDM (2021)
Keyphrases
- graph structure
- directed graph
- neural network
- pattern recognition
- finding the shortest path
- graph classification
- undirected graph
- graph matching
- graph theory
- graph model
- structural pattern recognition
- graph theoretic
- graph representation
- graph databases
- classification accuracy
- class imbalance
- graph mining
- random graphs
- labeled graphs
- tree structure
- graph theoretical
- weighted graph
- graph structures
- support vector
- decision trees
- multi layer perceptron
- edge weights
- graph partitioning
- graph construction
- connected components
- graph representations
- feature space
- support vector machine
- graph isomorphism
- subgraph isomorphism
- graph search
- graph clustering
- graph data
- artificial neural networks
- imbalanced data
- imbalanced datasets
- adjacency matrix
- spanning tree
- training process
- imbalanced data sets
- bipartite graph
- query graph
- training samples
- random walk
- feature selection