Amazon Beauty

Overview

Dataset name: Amazon Beauty
Latest version: 2023
Available versions: 2023
Source: https://amazon-reviews-2023.github.io/

A large-scale Amazon Reviews dataset, collected by McAuley Lab

Citation

@article{DBLP:journals/corr/abs-2403-03952,
author       = {Yupeng Hou and
                Jiacheng Li and
                Zhankui He and
                An Yan and
                Xiusi Chen and
                Julian J. McAuley},
title        = {Bridging Language and Items for Retrieval and Recommendation},
journal      = {CoRR},
volume       = {abs/2403.03952},
year         = {2024}
}

Version: 2023

Data Sources

Name	Source type	Archive	URL	Checksum
ratings	HttpSource	gz	https://mcauleylab.ucsd.edu/public_datasets/data/amazon_2023/benchmark/0core/rating_only/Beauty_and_Personal_Care.csv.gz	md5:6b9dfce7fca70dd05e1bcf77c1953c40

Resources

ratings

Type: interactions
Format: transactions_tabular
Required: yes
Source: ratings
Filename: Beauty_and_Personal_Care.csv

Schema

sep: ','
user_col: user_id
item_col: parent_asin
rating_col: rating
timestamp_col: timestamp
header: 0

Dataset Characteristics

Computed at: 2025-12-15

Metric	Value
n_users	11325787
n_items	1028731
n_interactions	23591312
space_size	3413.383685772374
space_size_log	3.5331851084509505
shape	11.009473808021728
shape_log	1.0417665625926829
density	2.024798812171433e-06
density_log	-5.693618122624369
gini_item	0.8549725671297695
gini_user	0.42172362782257544
ratings_per_user	2.0829733068439307
ratings_per_item	22.932440064506658

License & Usage

Please refer to the official dataset page for licensing and usage restrictions. https://amazon-reviews-2023.github.io/