Using Graph and Vertex Entropy to Compare Empirical Graphs with Theoretical Graph Models.
Tomasz KajdanowiczMikolaj MorzyPublished in: Entropy (2016)
Keyphrases
- labeled graphs
- directed graph
- undirected graph
- edge weights
- attributed graphs
- maximum cardinality
- weighted graph
- graph theory
- graph representation
- theoretical analysis
- graph structure
- vertex set
- bipartite graph
- hamiltonian cycle
- graph theoretic
- graph construction
- average degree
- graph model
- connected subgraphs
- graph structures
- graph clustering
- graph mining
- graph matching
- graph data
- subgraph isomorphism
- graph kernels
- graph databases
- random graphs
- series parallel
- minimum weight
- adjacency matrix
- graph theoretical
- graph search
- information theoretic
- graph partitioning
- graph classification
- spanning tree
- graph properties
- betweenness centrality
- random walk
- strongly connected
- directed acyclic graph
- connected dominating set
- graph patterns
- mutual information
- dynamic graph
- planar graphs
- connected graphs
- directed acyclic
- structural pattern recognition
- graph isomorphism
- phase transition
- real world graphs
- web graph
- graph transformation
- connected components
- bounded treewidth
- minimum spanning tree
- complex networks
- dense subgraphs
- topological information
- maximum common subgraph
- inexact graph matching
- finding the shortest path
- query graph
- reachability queries
- adjacency graph
- graph drawing
- polynomial time complexity
- approximation algorithms