Approximate greedy clustering and distance selection for graph metrics.
David EppsteinSariel Har-PeledAnastasios SidiropoulosPublished in: J. Comput. Geom. (2020)
Keyphrases
- graph theoretic
- graph clustering
- distance computation
- clustering algorithm
- clustering method
- distance metric
- graph model
- graph partitioning
- distance measure
- greedy algorithm
- dissimilarity measure
- k means
- graph theory
- distance function
- inter cluster
- graph representation
- random selection
- proximity measures
- graph structure
- tree edit distance
- graph construction
- forward selection
- weighted graph
- hierarchical clustering
- spectral clustering
- search algorithm
- euclidean distance
- bipartite graph
- graph matching
- fuzzy clustering
- random walk
- intra cluster
- directed graph
- spectral methods
- graph layout
- feature selection
- graph properties
- euclidean metric
- unsupervised learning
- structured data
- distance matrix
- data clustering
- data objects
- path length
- normalized cut
- edge weights
- evaluation metrics