Turning Big Data Into Tiny Data: Constant-Size Coresets for k-Means, PCA, and Projective Clustering.
Dan FeldmanMelanie SchmidtChristian SohlerPublished in: SIAM J. Comput. (2020)
Keyphrases
- big data
- k means
- data processing
- spectral clustering
- data analysis
- data sets
- clustering algorithm
- high volume
- data sources
- data points
- data visualization
- big data analytics
- massive data
- cloud computing
- data management
- knowledge discovery
- clustering method
- data mining techniques
- data stores
- database
- business intelligence
- data warehousing
- raw data
- decision support
- data mining applications
- principal component analysis
- digital data
- clustering result