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cs.DS2019★ 2 cited
S-RASTER: Contraction Clustering for Evolving Data Streams
Gregor Ulm, Simon Smith, Adrian Nilsson +2
Contraction Clustering (RASTER) is a single-pass algorithm for density-based clustering of 2D data. It can process arbitrary amounts of data in linear time and in constant memory,…
cs.DS2019
Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass
Gregor Ulm, Simon Smith, Adrian Nilsson +2
Clustering is an essential data mining tool for analyzing and grouping similar objects. In big data applications, however, many clustering algorithms are infeasible due to their hi…