# caserec/Datasets-for-Recommender-Systems

This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS)

Repository: https://github.com/caserec/Datasets-for-Recommender-Systems
Canonical: https://ross.abutalabs.com/products/datasets-for-recommender-systems
Language: Jupyter Notebook
License Family: other
Topics: recommender-systems, datasets, public-data, database, data-science
Last push: 2023-08-28T21:59:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3496, "days_push": 1101, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1105, forks 177 (observed 2026-08-28T04:03:36.398992+00:00)

## What it is
A curated collection of public datasets for recommender systems research, spanning domains like books, movies, music, e-commerce, and dating. It links to well-known sources such as MovieLens, Amazon reviews, and LastFM, with descriptions and some pre-processed academic variants.

## Use cases
- find datasets to benchmark recommender system algorithms
- download MovieLens-style rating data for collaborative filtering experiments
- get e-commerce click and purchase logs for recommendation research
- locate music listening datasets for implicit feedback models
- find pre-processed datasets for academic RS papers

## When to choose
- you need real-world rating or interaction data to train or evaluate recommendation models
- you want a quick index of well-known recommender system datasets across domains
- you are doing academic experiments and want pre-processed benchmark data

## When to avoid
- you need a software library or tool rather than data
- you require guaranteed open licenses - some listed datasets need permission or citation
- you need actively maintained or freshly updated datasets

## Facets
- artifact type: dataset
- maturity: maintenance
- function: data-science
- domain: data-science, machine-learning
- platform: cross-platform
- tags: recommender-systems, datasets, curated-list, public-data, collaborative-filtering

## Member repositories
- caserec/Datasets-for-Recommender-Systems (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:36.398992+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:44:21.274784+00:00, confidence not recorded.
  - readme: https://github.com/caserec/Datasets-for-Recommender-Systems (fetched 2026-08-28T04:03:36.398992+00:00, sha 386ecf7fd6ba)
- Data as of 2026-08-30T08:39:29.467469+00:00.