A rapid review of clustering algorithms
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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
6Topics & keywords
Topics
Keywords
- Cluster analysis
- Computer science
- Data mining
- Field (mathematics)
- Set (abstract data type)
- CURE data clustering algorithm
- Strengths and weaknesses
- Correlation clustering
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