Open Graph Benchmark: Datasets for Machine Learning on Graphs.
Weihua HuMatthias FeyMarinka ZitnikYuxiao DongHongyu RenBowen LiuMichele CatastaJure LeskovecPublished in: CoRR (2020)
Keyphrases
- benchmark datasets
- machine learning
- graph representation
- graph theory
- directed graph
- graph structure
- graph databases
- graph construction
- weighted graph
- graph matching
- graph structures
- graph mining
- labeled graphs
- graph theoretical
- graph model
- graph theoretic
- graph partitioning
- graph classification
- graph search
- series parallel
- adjacency matrix
- random graphs
- graph properties
- graph clustering
- structural pattern recognition
- undirected graph
- graph kernels
- graph representations
- subgraph isomorphism
- graph data
- spanning tree
- graph isomorphism
- dynamic graph
- graph layout
- bipartite graph
- semi supervised learning
- uci machine learning repository
- maximum clique
- connected graphs
- maximal cliques
- neighborhood graph
- maximum common subgraph
- uci repository
- ensemble methods
- finding the shortest path
- machine learning algorithms
- machine learning methods
- web graph
- graph patterns
- bounded treewidth
- text mining
- adjacency graph
- random walk
- minimum spanning tree
- structured data
- planar graphs
- decision trees
- massive graphs
- directed acyclic graph
- real world graphs
- edge weights
- dense subgraphs
- reachability queries
- learning algorithm
- knn
- web search
- text classification
- query graph
- connected components
- topological information
- small world
- frequent subgraphs