RcppHungarian (R package): papers linking to it

CRAN · CRAN.R-project.org/package=RcppHungarian

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to RcppHungarian (R package) (https://CRAN.R-project.org/package=RcppHungarian), 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.

Key findings#

3 papers in the tracked journals link to RcppHungarian (R package) in their Crossref records, the first in 2023; most of them (2) in 2025.
By category: Statistics (2) and Operations Research (1); the journals with the most are Annals of Operations Research (1), Statistical Papers (1) and Computational Statistics (1).
3 of the papers build on one another: a later paper cites an earlier one that also links RcppHungarian (R package).

By year#

20232025

Papers linking to RcppHungarian (R package) by publication year
Year	Papers
2023	1
2025	2

Journals#

Journals whose papers link to RcppHungarian (R package) most
Journal	Papers
Annals of Operations Research	1
Statistical Papers	1
Computational Statistics	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Variational Bayes estimation of hierarchical Dirichlet-multinomial mixtures for text clustering Computational Statistics, 2023
- Stochastic variational inference for clustering short text data with finite mixtures of Dirichlet-Multinomial distributions Statistical Papers, 2025 — cites the paper above
  - Hierarchical mixtures of Unigram models for short text clustering: the role of Beta-Liouville priors Annals of Operations Research, 2025 — cites the paper above

Papers linking to RcppHungarian (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2023-05-15	Variational Bayes estimation of hierarchical Dirichlet-multinomial mixtures for text clustering	Computational Statistics	Massimo Bilancia, Michele Di Nanni, Fabio Manca et al.	8	cites it
2025-04-25	Stochastic variational inference for clustering short text data with finite mixtures of Dirichlet-Multinomial distributions	Statistical Papers	Massimo Bilancia, Andrea Nigri, Samuele Magro	2	cites it
2025-06-24	Hierarchical mixtures of Unigram models for short text clustering: the role of Beta-Liouville priors	Annals of Operations Research	Massimo Bilancia, Samuele Magro	2	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). RcppHungarian (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-rcpphungarian

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

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