Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks.
Yuhang YaoCarlee Joe-WongPublished in: AAAI (2021)
Keyphrases
- graph theoretic
- graph clustering
- dynamic graph
- neural network
- graph partitioning
- graph model
- graph construction
- graph representation
- graph theory
- dynamic networks
- weighted graph
- feed forward
- clustering method
- pattern recognition
- spectral graph
- graph properties
- adjacency matrix
- graph classification
- graph databases
- graph layout
- graph structure
- structural pattern recognition
- undirected graph
- graph mining
- random graphs
- clustering algorithm
- bipartite graph
- recurrent neural networks
- graph structures
- graph matching
- labeled graphs
- attributed graphs
- artificial neural networks
- spectral methods
- self organizing maps
- directed graph
- community discovery
- series parallel
- k means
- spanning tree
- graph theoretical
- graph kernels
- graph data
- subgraph isomorphism
- connected graphs
- reachability queries
- social networks
- edge weights
- community detection
- similarity function
- spectral clustering
- data clustering
- evolving graphs
- directed acyclic
- data points
- knn
- back propagation
- dense subgraphs
- connected components
- neighborhood graph
- polynomial time complexity
- data objects
- minimum spanning tree