A survey on clustering density based data stream algorithms

Research output: Contribution to journalArticle

Abstract

With the rapid evolution of technology, data size has increased as well. Thus, open the door to a new challenge of finding patterns such as the limitation of memory and time and the one pass to the whole data. Many clustering techniques has been developed to overcome these issues. Streaming data evolve with time, and that makes it almost impossible to define clusters number in that data. Density-based algorithm is one of the significant data clustering class to overcome this issue due to it doesn't require an advance knowledge about the number of clusters. This paper reviewed some of the existing density-based clustering algorithms for the data stream with the measurement used to evaluate the algorithm.

Original languageEnglish
Pages (from-to)147-153
Number of pages7
JournalInternational Journal of Engineering and Technology(UAE)
Volume7
Issue number4.36 Special Issue 36
Publication statusPublished - 1 Jan 2018

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Cluster Analysis
Clustering algorithms
Data storage equipment
Technology
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Keywords

  • Clustering
  • Data mining
  • Density-based clustering
  • Grid-based clustering
  • Micro-clustering
  • Stream data clustering

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • Chemical Engineering(all)
  • Engineering(all)
  • Hardware and Architecture

Cite this

A survey on clustering density based data stream algorithms. / Aljibawi, Mayas; Ahmad Nazri, Mohd Zakree; Othman, Zalinda.

In: International Journal of Engineering and Technology(UAE), Vol. 7, No. 4.36 Special Issue 36, 01.01.2018, p. 147-153.

Research output: Contribution to journalArticle

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