GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions.
Hanchen WangDefu LianYing ZhangLu QinXuemin LinPublished in: IJCAI (2020)
Keyphrases
- neural network
- structured data
- graph representation
- graph theory
- graph structure
- graph structures
- directed graph
- graph matching
- graph construction
- labeled graphs
- weighted graph
- graph mining
- graph databases
- graph data
- graph theoretic
- graph clustering
- adjacency matrix
- graph model
- random graphs
- graph classification
- graph partitioning
- graph properties
- graph theoretical
- subgraph isomorphism
- series parallel
- graph transformation
- graph isomorphism
- undirected graph
- structural pattern recognition
- bipartite graph
- graph kernels
- graph search
- inexact graph matching
- maximum common subgraph
- reachability queries
- graph layout
- dense subgraphs
- directed acyclic
- dynamic graph
- spanning tree
- artificial neural networks
- connected graphs
- graph representations
- knn
- minimum spanning tree
- graph embedding
- social graphs
- directed acyclic graph
- evolving graphs
- back propagation
- web graph
- maximum cardinality
- attributed graphs
- random walk
- connected components
- adjacency graph
- small world
- connected dominating set
- finding the shortest path
- proximity graph
- bounded treewidth
- graph drawing
- polynomial time complexity
- neighborhood graph
- maximum clique
- topological information
- maximal cliques
- edge weights
- real world graphs
- community detection
- query graph
- functional modules
- frequent subgraphs
- network properties
- shortest path
- planar graphs