Using Clustering and Blade Clusters in the Terabyte Task.
Giuseppe AttardiAndrea EsuliChirag PatelPublished in: TREC (2004)
Keyphrases
- clustering algorithm
- hierarchical clustering
- overlapping clusters
- cluster analysis
- data clustering
- clustering scheme
- k means
- clustering method
- fuzzy clustering
- self organizing maps
- unsupervised clustering
- incremental clustering
- document clustering
- clustering approaches
- density based clustering
- data points
- graph clustering
- model based clustering
- cluster centers
- disjoint clusters
- inter cluster
- affinity propagation
- homogeneous groups
- agglomerative hierarchical clustering
- cluster validation
- cluster membership
- density based clustering algorithm
- constrained clustering
- fuzzy k means
- hierarchical clustering algorithm
- agglomerative clustering
- clustering framework
- unsupervised learning
- arbitrary shape
- clustering quality
- cluster validity
- kohonen self organizing maps
- clustering result
- clustering analysis
- subspace clustering
- categorical data
- validity measures
- spectral clustering
- cluster structure
- similar objects
- clusters of arbitrary shapes
- search results clustering
- validity index
- soft clustering
- fuzzy c means
- intra cluster
- arbitrary shaped
- meaningful clusters
- data objects
- partial replication
- hierarchical agglomerative clustering
- high dimensional data
- cluster labels
- affinity measure
- spatial clustering
- synthetic datasets
- high dimensional datasets