instacart-market-basket-analysis: papers linking to it

Kaggle · www.kaggle.com/competitions/instacart-market-basket-analysis

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to instacart-market-basket-analysis (https://www.kaggle.com/competitions/instacart-market-basket-analysis), 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 the Kaggle dataset instacart-market-basket-analysis in their Crossref records, the first in 2021; most of them (2) in 2025.
By category: AI (2) and Operations Research (1); the journals with the most are Expert Systems with Applications (1), Neural Computing and Applications (1) and Transportation Research Part E Logistics and Transportation Review (1).

By year#

20212025

Papers linking to instacart-market-basket-analysis by publication year
Year	Papers
2021	1
2025	2

Journals#

Journals whose papers link to instacart-market-basket-analysis most
Journal	Papers
Expert Systems with Applications	1
Neural Computing and Applications	1
Transportation Research Part E Logistics and Transportation Review	1

Papers linking to instacart-market-basket-analysis, most cited first
Published	Title	Journal	Authors	Citations	Link
2021-05-28	Scalable multi-product inventory control with lead time constraints using reinforcement learning	Neural Computing and Applications	Hardik Meisheri, Nazneen N. Sultana, Mayank Baranwal et al.	38	cites it
2025-06-06	Enhancing customer retention in Online Retail through churn prediction: A hybrid RFM, K-means, and deep neural network approach	Expert Systems with Applications	Maha Zaghloul, Sherif Barakat, Amira Rezk	29	cites it
2025-12-20	Multi-objective, multi-attribute fleet sizing in a dynamic and stochastic environment: A data-driven approach	Transportation Research Part E Logistics and Transportation Review	Christian Truden, Mike Hewitt	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). instacart-market-basket-analysis: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-instacart-market-basket-analysis

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

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