Turning Big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering.
Dan FeldmanMelanie SchmidtChristian SohlerPublished in: CoRR (2018)
Keyphrases
- big data
- k means
- data analysis
- spectral clustering
- data processing
- clustering algorithm
- data sets
- high volume
- vast amounts of data
- data visualization
- massive data
- knowledge discovery
- hierarchical clustering
- data management
- principal component analysis
- clustering result
- high dimensional data
- data clustering
- data warehousing
- cluster analysis
- clustering method
- data points
- information retrieval
- business intelligence
- dimensionality reduction
- predictive modeling
- digital data
- end users
- data stores