A streaming clustering approach using a heterogeneous system for big data analysis

Abstract

Data clustering is a fundamental challenge in data analytics. It is the main task in exploratory data mining and a core technique in machine learning. As the volume, variety, velocity, and variability of data grows, we need more efficient data analysis methods that can scale towards increasingly large and high dimensional data sets. We develop a streaming… (More)
DOI: 10.1109/ICCAD.2017.8203845

Topics

14 Figures and Tables

Cite this paper

@article{Lee2017ASC, title={A streaming clustering approach using a heterogeneous system for big data analysis}, author={Dajung Lee and Alric Althoff and Dustin Richmond and Ryan Kastner}, journal={2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)}, year={2017}, pages={699-706} }