GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks.
Tianxiang ZhaoXiang ZhangSuhang WangPublished in: CoRR (2021)
Keyphrases
- directed graph
- graph structure
- neural network
- pattern recognition
- graph classification
- finding the shortest path
- undirected graph
- graph matching
- graph representation
- graph structures
- weighted graph
- graph theory
- graph mining
- graph theoretic
- edge weights
- graph model
- graph construction
- graph kernels
- series parallel
- graph clustering
- structural pattern recognition
- nodes of a graph
- classification accuracy
- graph databases
- class imbalance
- random walk
- decision trees
- bipartite graph
- graph theoretical
- graph partitioning
- imbalanced data sets
- support vector machine
- adjacency matrix
- web graph
- feature selection
- spanning tree
- support vector
- graph data
- subgraph isomorphism
- random graphs
- root node
- graph representations
- training process
- class labels
- labeled graphs
- betweenness centrality
- graph isomorphism
- dynamic graph
- reachability queries
- tree structure
- connected graphs
- imbalanced datasets