Non-Linear Cluster Enhancement: Forcing Clusters into a Compact Shape.
Benjamin SchellingLukas MiklautzClaudia PlantPublished in: ECAI (2020)
Keyphrases
- clustering algorithm
- arbitrary shape
- inter cluster
- overlapping clusters
- hierarchical clustering
- disjoint clusters
- cluster analysis
- data clustering
- clustering framework
- intra cluster
- data points
- cluster centers
- density based clustering
- unsupervised clustering
- hierarchical agglomerative clustering
- subspace clustering
- clustering procedure
- clustering quality
- agglomerative hierarchical clustering
- cluster validity
- cluster structure
- clustering scheme
- constrained clustering
- subspace clusters
- model based clustering
- proximity graph
- k means
- shape features
- document clusters
- shape model
- cluster membership
- gene clusters
- fuzzy c means
- clustering result
- hierarchical structure
- hierarchical clustering algorithm
- meaningful clusters
- image processing
- clustering approaches
- initial set
- fuzzy clustering
- data objects
- homogeneous groups
- shape representation
- shape matching
- shape descriptors
- image enhancement
- cluster validation
- semi supervised
- self organizing maps
- hierarchical clustering algorithms
- document clustering
- feature vectors
- shape analysis
- multiscale
- cluster ensemble