---
title: "dbscan (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to dbscan (R package) in their Crossref records, the first in 2019; most of them (2) in 2019."
url: https://scholar4ai.com/code/cran-dbscan
markdown_url: https://scholar4ai.com/code/cran-dbscan.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to dbscan (R package) in their Crossref records, the first in 2019; most of them (2) in 2019. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# dbscan (R package): papers linking to it

Research papers in the 480 tracked journals that link to dbscan (R package) (https://CRAN.R-project.org/package=dbscan), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- CRAN
- https://CRAN.R-project.org/package=dbscan

All repositories: https://scholar4ai.com/code.md

## Key findings

- 5 papers in the tracked journals link to dbscan (R package) in their Crossref records, the first in 2019; most of them (2) in 2019.
- By category: Statistics (3) and AI (2); the journals with the most are Computational Statistics (1), Statistics and Computing (1) and Computational Statistics & Data Analysis (1).

## By year

*Papers linking to dbscan (R package) by publication year*

| Year | Papers |
|---|---:|
| 2019 | 2 |
| 2023 | 1 |
| 2025 | 1 |
| 2026 | 1 |

## Journals

*Journals whose papers link to dbscan (R package) most*

| Journal | Papers |
|---|---:|
| [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | 1 |
| [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | 1 |
| [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | 1 |
| [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | 1 |
| [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | 1 |

## Papers

*Papers linking to dbscan (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2019-01-27 | [A machine learning based intrusion detection scheme for data fusion in mobile clouds involving heterogeneous client networks](https://doi.org/10.1016/j.inffus.2019.01.002) | [Information Fusion](https://scholar4ai.com/journals/information-fusion.md) | Saurabh Dey, Qiang Ye, Srinivas Sampalli | 95 | cites it |
| 2019-11-21 | [On normalization and algorithm selection for unsupervised outlier detection](https://doi.org/10.1007/s10618-019-00661-z) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Sevvandi Kandanaarachchi, Mario Andrés Muñoz, Rob J. Hyndman et al. | 62 | cites it |
| 2023-11-24 | [Randomized self-updating process for clustering large-scale data](https://doi.org/10.1007/s11222-023-10355-8) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Shang‐Ying Shiu, Yen-Shiu Chin, Szu‐Han Lin et al. | 0 | cites it |
| 2025-12-29 | [Efficient subsampling for exponential family models](https://doi.org/10.1016/j.csda.2025.108336) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Subhadra Dasgupta, Holger Dette | 0 | cites it |
| 2026-04-16 | [Area-based epigraph and hypograph indices for functional outlier detection](https://doi.org/10.1007/s00180-026-01731-9) | [Computational Statistics](https://scholar4ai.com/journals/computational-statistics.md) | Belén Pulido, Alba M. Franco‐Pereira, Rosa Elvira Lillo et al. | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). dbscan (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-dbscan

```bibtex
@misc{scholar4ai-code-cran-dbscan,
  author = {{Scholar4AI}},
  title = {dbscan (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-dbscan}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).