Omkar2118/datasets huggingface dataset:
OTTO Recommender Systems Dataset

The `OTTO` session dataset is a large-scale dataset intended for multi-objective recommendation research. We collected the data from anonymized behavior logs of the [OTTO](https://otto.de) webshop and the app. The mission of this dataset is to serve as a benchmark for session-based recommendations and foster research in the multi-objective and session-based recommender systems area. We also launched a [Kaggle competition](https://www.kaggle.com/competitions/otto-recommender-system) with the goal to predict clicks, cart additions, and orders based on previous events in a user session.

For additional background, please see the published [OTTO Recommender Systems Dataset](https://github.com/otto-de/recsys-dataset) GitHub.

## Key Features

- 12M real-world anonymized user sessions
- 220M events, consiting of `clicks`, `carts` and `orders`
- 1.8M unique articles in the catalogue
- Ready to use data in `.jsonl` format
- Evaluation metrics for multi-objective optimization

## Dataset Statistics

| Dataset |  #sessions |    #items |     #events |     #clicks |     #carts |   #orders | Density [%] |
| :------ | ---------: | --------: | ----------: | ----------: | ---------: | --------: | ----------: |
| Train   | 12.899.779 | 1.855.603 | 216.716.096 | 194.720.954 | 16.896.191 | 5.098.951 |      0.0005 |
| Test    |  1.671.803 | 1.019.357 |  13.851.293 |  12.340.303 |  1.155.698 |   355.292 |      0.0005 |