reviewArrayMay 1, 2026GOLD OA

A rapid review of clustering algorithms

Indexed inarxivcrossrefdatacitedoaj

Abstract

Clustering algorithms aim to organize data into groups or clusters based on the inherent patterns and similarities within the data. They play an important role in today's life, such as in marketing and e-commerce, healthcare, data organization and analysis, and social media. Numerous clustering algorithms exist, with ongoing developments introducing new ones. Each algorithm possesses its own set of strengths and weaknesses, and as of now, there is no universally applicable algorithm for all tasks. In this work, we analyzed existing clustering algorithms and classify mainstream algorithms across five different dimensions: underlying principles and characteristics, data point assignment to clusters, dataset…

Citation impact

10
total citations
FWCI
25.07
Percentile
98%
References
0
Citations per year

Authors

6

Topics & keywords

Keywords
  • Cluster analysis
  • Computer science
  • Data mining
  • Field (mathematics)
  • Set (abstract data type)
  • CURE data clustering algorithm
  • Strengths and weaknesses
  • Correlation clustering
No related works found for this paper.

Funding