A density-based statistical analysis of graph clustering algorithm performance.
Pierre MiasnikofAlexander Y. ShestopaloffAnthony J. BonnerYuri LawryshynPanos M. PardalosErnesto EstradaPublished in: J. Complex Networks (2020)
Keyphrases
- clustering algorithm
- statistical analysis
- maximum spanning tree
- graph partitioning
- k means
- clustering method
- graph clustering
- density based clustering
- arbitrary shape
- data clustering
- agglomerative clustering
- partitioning algorithm
- subspace clustering
- fuzzy c means
- graph theory
- bipartite graph
- graph structure
- connected components
- spatial clustering
- normalized cut
- statistical methods
- graph representation
- graph mining
- graph model
- graph databases
- cluster analysis
- density based clustering algorithm
- np complete
- similarity matrix
- directed acyclic graph
- dependency graph
- clustering analysis
- clinical data
- link analysis
- graph matching
- hierarchical clustering
- spectral clustering
- random walk
- pairwise