Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks.
Yuhang YaoCarlee Joe-WongPublished in: CoRR (2020)
Keyphrases
- graph theoretic
- graph clustering
- dynamic graph
- neural network
- graph partitioning
- graph construction
- graph model
- graph theory
- graph structure
- dynamic networks
- graph representation
- weighted graph
- graph matching
- recurrent neural networks
- graph databases
- labeled graphs
- directed graph
- clustering algorithm
- graph layout
- graph properties
- graph mining
- random graphs
- clustering method
- bipartite graph
- feed forward
- self organizing maps
- pattern recognition
- graph structures
- graph search
- graph theoretical
- adjacency matrix
- graph data
- minimum spanning tree
- structural pattern recognition
- k means
- spectral methods
- series parallel
- graph classification
- graph kernels
- spanning tree
- spectral clustering
- data objects
- directed acyclic
- back propagation
- artificial neural networks
- evolving graphs
- graph isomorphism
- adjacency graph
- normalized cut
- undirected graph
- similarity function
- topological information
- planar graphs
- bounded treewidth
- subgraph isomorphism
- community discovery
- neighborhood graph
- dense subgraphs
- complex networks
- spectral graph
- network structure
- social networks