Clustering of high dimensional data streams

  • Authors:
  • Sotiris K. Tasoulis;Dimirtis K. Tasoulis;Vassilis P. Plagianakos

  • Affiliations:
  • Department of Computer Science and Biomedical Informatics, University of Central Greece, Lamia, Greece;Winton Capital Management, United Kingdom;Department of Computer Science and Biomedical Informatics, University of Central Greece, Lamia, Greece

  • Venue:
  • SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Clustering of data streams has become a task of great interest in the recent years as such data formats is are becoming increasingly ambiguous. In many cases, these data are also high dimensional and in result more complex for clustering. As such there is a growing need for algorithms that can be applied on streaming data and the at same time can cope with high dimensionality. To this end, here we design a streaming clustering approach by extending a recently proposed high dimensional clustering algorithm.