The Big Picture: Understanding large-scale graphs using Graph Grouping with Gradoop.
Martin JunghannsAndré PetermannNiklas TeichmannErhard RahmPublished in: BTW (2017)
Keyphrases
- big picture
- graph partitioning
- graph model
- graph representation
- graph structure
- massive graphs
- graph theory
- graph matching
- graph structures
- weighted graph
- directed graph
- graph classification
- graph databases
- adjacency matrix
- labeled graphs
- graph construction
- graph mining
- graph theoretic
- graph properties
- graph clustering
- series parallel
- graph data
- bipartite graph
- graph theoretical
- graph representations
- reachability queries
- graph isomorphism
- random graphs
- subgraph isomorphism
- graph search
- real world
- real world graphs
- undirected graph
- graph kernels
- planar graphs
- finding the shortest path
- maximum clique
- normalized cut
- dynamic graph
- connected graphs
- graph mining algorithms
- expert systems
- graph patterns
- edge weights
- web graph
- spanning tree
- structured data
- graph layout
- case study
- small world
- directed acyclic graph
- connected components
- database design
- random walk
- object oriented
- metadata
- machine learning