Explaining Graph Neural Networks for Node Similarity on Graphs.
Daniel DazaCuong Xuan ChuTrung-Kien TranDaria StepanovaMichael CochezPaul GrothPublished in: CoRR (2024)
Keyphrases
- graph structure
- directed graph
- neural network
- maximum common subgraph
- finding the shortest path
- undirected graph
- edge weights
- graph structures
- weighted graph
- inexact graph matching
- labeled graphs
- subgraph isomorphism
- graph representation
- graph theory
- similarity function
- similarity graph
- adjacency matrix
- graph matching
- graph mining
- graph databases
- graph model
- densely connected
- graph clustering
- normalized cut
- nodes of a graph
- similarity measure
- graph properties
- graph theoretic
- graph theoretical
- random walk
- edit distance
- graph classification
- graph representations
- graph construction
- structural pattern recognition
- bipartite graph
- topological information
- pattern recognition
- graphical models
- graph isomorphism
- random graphs
- graph data
- spanning tree
- minimum spanning tree
- artificial neural networks
- graph partitioning
- betweenness centrality
- strongly connected
- degree distribution
- small world networks
- similarity scores
- connected graphs
- shortest path
- graph kernels
- maximal cliques
- graph search
- directed acyclic graph
- connected components
- series parallel
- small world
- dynamic graph
- graph patterns
- web graph
- power law
- complex networks
- query graph