Accurate and Scalable Graph Neural Networks for Billion-Scale Graphs.
Juxiang ZengPinghui WangLin LanJunzhou ZhaoFeiyang SunJing TaoJunlan FengMin HuXiaohong GuanPublished in: ICDE (2022)
Keyphrases
- neural network
- graph representation
- graph matching
- graph structure
- graph theory
- weighted graph
- directed graph
- labeled graphs
- graph theoretic
- graph databases
- bipartite graph
- pattern recognition
- graph theoretical
- adjacency matrix
- graph construction
- graph clustering
- graph model
- structural pattern recognition
- graph classification
- graph partitioning
- graph properties
- minimum spanning tree
- graph structures
- spanning tree
- random graphs
- graph mining
- undirected graph
- dynamic graph
- subgraph isomorphism
- graph isomorphism
- graph search
- series parallel
- graph data
- dense subgraphs
- maximal cliques
- planar graphs
- random walk
- graph transformation
- graph representations
- finding the shortest path
- graph drawing
- graph embedding
- average degree
- inexact graph matching
- reachability queries
- maximum cardinality
- connected graphs
- polynomial time complexity
- graph mining algorithms
- adjacency graph
- frequent subgraphs
- neighborhood graph
- graph patterns
- graph kernels
- edge weights
- social graphs
- real world graphs
- strongly connected
- topological information
- structured data
- community discovery
- graph layout
- web graph