High-Order Topology-Enhanced Graph Convolutional Networks for Dynamic Graphs.
Jiawei ZhuBo LiZhenshi ZhangLing ZhaoHaifeng LiPublished in: Symmetry (2022)
Keyphrases
- high order
- dynamic networks
- small world
- dynamic graph
- fully connected
- higher order
- graph structures
- average degree
- edge weights
- graph representation
- community discovery
- highly connected
- graph mining
- social networks
- real world graphs
- pairwise
- graph matching
- random graphs
- network structure
- graph theory
- bipartite graph
- spanning tree
- labeled graphs
- graph clustering
- real world social networks
- low order
- graph model
- directed graph
- graph construction
- topological information
- graph layout
- complex networks
- degree distribution
- weighted graph
- graph structure
- adjacency matrix
- social graphs
- directed edges
- graph theoretic
- graph databases
- real world networks
- betweenness centrality
- fourth order
- power law
- random walk
- graph partitioning
- undirected graph
- community detection
- directed acyclic graph
- densely connected
- markov random field
- lower order
- graph data
- protein interaction networks
- shortest path
- graph properties
- tensor analysis
- web graph
- clustering coefficient
- prediction accuracy
- graph kernels
- reachability queries
- support vector