---
title: "rossmann-store-sales: papers citing this dataset"
description: "6 papers in the tracked journals link to the Kaggle dataset rossmann-store-sales in their Crossref records, the first in 2020; most of them (2) in 2025."
url: https://scholar4ai.com/code/kaggle-competition-rossmann-store-sales
markdown_url: https://scholar4ai.com/code/kaggle-competition-rossmann-store-sales.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "6 papers in the tracked journals link to the Kaggle dataset rossmann-store-sales in their Crossref records, the first in 2020; most of them (2) in 2025. (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)
---

# rossmann-store-sales: papers linking to it

Research papers in the 480 tracked journals that link to rossmann-store-sales (https://www.kaggle.com/competitions/rossmann-store-sales), 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.

- Kaggle
- https://www.kaggle.com/competitions/rossmann-store-sales

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

## Key findings

- 6 papers in the tracked journals link to the Kaggle dataset rossmann-store-sales in their Crossref records, the first in 2020; most of them (2) in 2025.
- By category: AI (4), Operations Research (1) and Management (1); the journals with the most are Machine Learning (2), Computers & Industrial Engineering (1) and Journal of Business Research (1).

## By year

*Papers linking to rossmann-store-sales by publication year*

| Year | Papers |
|---|---:|
| 2020 | 1 |
| 2021 | 1 |
| 2023 | 1 |
| 2024 | 1 |
| 2025 | 2 |

## Journals

*Journals whose papers link to rossmann-store-sales most*

| Journal | Papers |
|---|---:|
| [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 2 |
| [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | 1 |
| [Journal of Business Research](https://scholar4ai.com/journals/journal-of-business-research.md) | 1 |
| [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 1 |
| [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 |

## Papers

*Papers linking to rossmann-store-sales, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-04-10 | [Survey on categorical data for neural networks](https://doi.org/10.1186/s40537-020-00305-w) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | John Hancock, Taghi M. Khoshgoftaar | 619 | cites it |
| 2021-07-08 | [Explainable boosted linear regression for time series forecasting](https://doi.org/10.1016/j.patcog.2021.108144) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Igor Ilic, Berk Görgülü, Mücahit Çevik et al. | 84 | cites it |
| 2023-03-13 | [SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting](https://doi.org/10.1007/s10994-023-06316-x) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Rakshitha Godahewa, Geoffrey I. Webb, Daniel Francis Schmidt et al. | 15 | cites it |
| 2024-07-03 | [Prediction-led prescription: Optimal Decision-Making in times of turbulence and business performance improvement](https://doi.org/10.1016/j.jbusres.2024.114805) | [Journal of Business Research](https://scholar4ai.com/journals/journal-of-business-research.md) | Andreas Schäfers, Vasileios Bougioukos, Georgios Karamatzanis et al. | 11 | cites it |
| 2025-02-24 | [TCR: topologically consistent reweighting for XGBoost in regression tasks](https://doi.org/10.1007/s10994-024-06704-x) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Monty-Maximilian Zühlke, Daniel Kudenko⋆ | 7 | cites it |
| 2025-06-11 | [Supply chain demand forecasting based on multi-time scale data fusion network](https://doi.org/10.1016/j.cie.2025.111324) | [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | Yipeng Chen, Heng Zhang, Xingyou Yan et al. | 6 | 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). rossmann-store-sales: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-rossmann-store-sales

```bibtex
@misc{scholar4ai-code-kaggle-competition-rossmann-store-sales,
  author = {{Scholar4AI}},
  title = {rossmann-store-sales: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-competition-rossmann-store-sales}},
  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/).