otto-de/recsys-dataset
🛍 A real-world e-commerce dataset for session-based recommender systems research.
This dataset provides real-world e-commerce browsing and purchasing data from the OTTO webshop and app. It includes anonymized user sessions with events like product clicks, items added to carts, and successful orders. E-commerce analysts and machine learning researchers can use this data to build and evaluate algorithms that recommend products to shoppers during their current visit.
372 stars. No commits in the last 6 months.
Use this if you need a large, industry-grade dataset to develop and benchmark session-based or sequential product recommendation systems for online retail.
Not ideal if you need a dataset that includes user demographics, purchase history across multiple sessions, or information beyond product interactions.
Stars
372
Forks
52
Language
Python
License
MIT
Category
Last pushed
May 14, 2025
Commits (30d)
0
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