The DOI matches its Crossref record; 26 of the 27 references it cites were found in a registry or an index.
Density-Based Clustering Based on Hierarchical Density Estimates
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Small values produce numerous small clusters potentially appearing only at extreme density thresholds, whereas larger values merge smaller groups into fewer, more stable clusters, that can potentially hide the variability of the patterns observed.”
From Ecological legacies of pre-columbian settlements evident in palm clusters of neotropical mountain forests (2026) · cites this paper as [65]
In the citing paper
“HDBSCAN is adept at clustering outputs from LLMs due to its ability to manage clusters with varied densities, autonomously identify the number of clusters, and filter out noise as outlier data.”
From Large language model trained on clinical oncology data predicts cancer progression (2025) · cites this paper as [54]
Citations
Cites
UCI Machine Learning Repository
Asuncion, A. (2007) · Medical Entomology and Zoology · Cited by 24,190
(1996) · Cited by 20,179
Self-citationHubert, L., & Arabie, P. (1985) · Journal of Classification · doi:10.1007/bf01908075 · Cited by 8,219
Chiu, S., & Tavella, D. (2008) · Routledge eBooks · doi:10.4324/9780080878096-12 · Cited by 6,987
(1975) · CERN Document Server (European Organization for Nuclear Research) · Cited by 5,958
Ankerst, M. (1999) · doi:10.1145/304181.304187 · Cited by 3,982
Self-citationThe Amsterdam Library of Object Images
Geusebroek, J., Burghouts, G. J., & Smeulders, A. W. M. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000042993.50813.60 · Cited by 919
Kriegel, H., Kröger, P., Sander, J., & Zimek, A. (2011) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.30 · Cited by 900
Self-citationFast and effective text mining using linear-time document clustering
Larsen, B., & Aone, C. (1999) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/312129.312186 · Cited by 869
Model-based clustering and data transformations for gene expression data
Yeung, K. Y., Fraley, C., Murua, A., Raftery, A. E., & Ruzzo, W. L. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.10.977 · Cited by 869
Cited by
Sorted by citations
Items 1,001–1,003 of 1,003
Settlement patterns and community delimitation in chibcha chiefdoms of Colombia and Panama
Rodríguez, L. M. S. (2026) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-026-09767-3 · Cited by 3
Fajardo, S., Mohammadi, S., Gregorio de Souza, J., Ardila, C., Tapscott, A., Heidgen, S., Mayorga Hernández, M. I., Mota de Oliveira, S., Montejo, F., Moderato, M., et al. (2026) · Scientific Reports · doi:10.1038/s41598-026-45976-2 · Cited by 1
When Agents Talk: Discourse, Manipulation, and Risk in an Agentic Social Network
Labs, 1., :, Cheong, G., Davis, V., Garcia, J., Gee, K., Hart, M., Hayes, N., Houghton, H., Lee, K., et al. (2026) · arXiv · doi:10.48550/arxiv.2606.00067
“Unlike methods such as k-means, HDBSCAN does not require a predefined number of clusters.”
Metadata
- Authors
- Campello, R. J. G. B., Moulavi, D., & Sander, J.
- Affiliations
- University of Alberta (CA)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2013
- Volume
- 7819
- Pages
- 160-172
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W151377110
- Cited by
- 2,680
- References
- 27
- Citations by year
- 2026: 413 · 2025: 497 · 2024: 404 · 2023: 337 · 2022: 271 · 2021: 253 · 2020: 181 · 2019: 148 · 2018: 84 · 2017: 50 · 2016: 24 · 2015: 9 · 2014: 9
- FWCI
- 9.26
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- ResearchOnline - JCU (James Cook University) (submittedVersion)
- Lecture Notes in Artificial Intelligence
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
- Physical Sciences › Computer Science › Information Systems › Data Management and Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
- Keywords
- density-based clustering, hierarchical clustering, density limit
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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