A Comprehensive Survey of Clustering Algorithms
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- Authors
- Xu, D., & Tian, Y.
- Affiliations
- Chinese Academy of Sciences (CN)
- Corresponding author
- Tian, Yingjie
- Venue
- Annals of Data Science
- Published
- 2015-06
- Volume
- 2
- Issue
- 2
- Pages
- 165-193
- ISSN
- 2198-5804 (ISSN-L)
- 2198-5812
- OpenAlex
- W1128809682
- Cited by
- 1,939
- References
- 144
- Citations by year
- 2026: 123 · 2025: 202 · 2024: 259 · 2023: 259 · 2022: 271 · 2021: 275 · 2020: 217 · 2019: 165 · 2018: 102 · 2017: 45 · 2016: 20 · 2015: 1
- FWCI
- 54.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Annals of Data Science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Keywords
- clustering algorithms, clustering, distance measures, similarity measures, clustering evaluation metrics, algorithm comparison
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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