daconjam/Recommender-System-Datasets
A list of compatible datasets, noting other major repositories containing popular real-world datasets, along with sample code for a range of recommendation tasks.
This collection of datasets provides various types of real-world information, like news articles, product reviews, and social network data, to help academics and researchers build and test recommender systems. You can input these raw datasets into your models and, after analysis, your system can recommend relevant news, products, or connections to users. It's designed for university researchers, faculty, and other scientists working on recommendation algorithms.
110 stars. No commits in the last 6 months.
Use this if you are an academic researcher needing free, public datasets and sample code to develop, test, or benchmark recommender systems for non-commercial research.
Not ideal if you need proprietary, highly specific commercial data or are looking for a plug-and-play recommender system solution rather than raw datasets for research.
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Aug 13, 2021
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