metadata
language:
- en
tags:
- recommendation
- reviews
size_categories:
- 10B<n<100B
dataset_info:
- config_name: raw_meta_All_Beauty
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 172622243
num_examples: 112590
download_size: 59635138
dataset_size: 172622243
- config_name: raw_meta_Arts_Crafts_and_Sewing
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 1893257069
num_examples: 801446
download_size: 806711170
dataset_size: 1893257069
- config_name: raw_meta_Cell_Phones_and_Accessories
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 3497596478
num_examples: 1288490
download_size: 1262072469
dataset_size: 3497596478
- config_name: raw_meta_Electronics
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 4603602269
num_examples: 1610012
download_size: 1955009715
dataset_size: 4603602269
- config_name: raw_meta_Gift_Cards
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 1740761
num_examples: 1137
download_size: 401887
dataset_size: 1740761
- config_name: raw_meta_Handmade_Products
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 340772183
num_examples: 164817
download_size: 132049123
dataset_size: 340772183
- config_name: raw_meta_Industrial_and_Scientific
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 986632649
num_examples: 427564
download_size: 425007659
dataset_size: 986632649
- config_name: raw_meta_Musical_Instruments
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 553296301
num_examples: 213593
download_size: 229633633
dataset_size: 553296301
- config_name: raw_meta_Toys_and_Games
features:
- name: main_category
dtype: string
- name: title
dtype: string
- name: average_rating
dtype: float64
- name: rating_number
dtype: int64
- name: features
sequence: string
- name: description
sequence: string
- name: price
dtype: string
- name: images
sequence:
- name: hi_res
dtype: string
- name: large
dtype: string
- name: thumb
dtype: string
- name: variant
dtype: string
- name: videos
sequence:
- name: title
dtype: string
- name: url
dtype: string
- name: user_id
dtype: string
- name: store
dtype: string
- name: categories
sequence: string
- name: details
dtype: string
- name: parent_asin
dtype: string
- name: bought_together
dtype: string
- name: subtitle
dtype: string
- name: author
dtype: string
splits:
- name: full
num_bytes: 2291736294
num_examples: 890874
download_size: 972667016
dataset_size: 2291736294
configs:
- config_name: raw_meta_All_Beauty
data_files:
- split: full
path: raw_meta_All_Beauty/full-*
- config_name: raw_meta_Arts_Crafts_and_Sewing
data_files:
- split: full
path: raw_meta_Arts_Crafts_and_Sewing/full-*
- config_name: raw_meta_Cell_Phones_and_Accessories
data_files:
- split: full
path: raw_meta_Cell_Phones_and_Accessories/full-*
- config_name: raw_meta_Electronics
data_files:
- split: full
path: raw_meta_Electronics/full-*
- config_name: raw_meta_Gift_Cards
data_files:
- split: full
path: raw_meta_Gift_Cards/full-*
- config_name: raw_meta_Handmade_Products
data_files:
- split: full
path: raw_meta_Handmade_Products/full-*
- config_name: raw_meta_Industrial_and_Scientific
data_files:
- split: full
path: raw_meta_Industrial_and_Scientific/full-*
- config_name: raw_meta_Musical_Instruments
data_files:
- split: full
path: raw_meta_Musical_Instruments/full-*
- config_name: raw_meta_Toys_and_Games
data_files:
- split: full
path: raw_meta_Toys_and_Games/full-*
Amazon Reviews 2023
Please also visit amazon-reviews-2023.github.io/ for more details, loading scripts, and preprocessed benchmark files.
[April 7, 2024] We add two useful files:
all_categories.txt: 34 lines (33 categories + "Unknown"), each line contains a category name.asin2category.json: A mapping betweenparent_asin(item ID) to its corresponding category name.
This is a large-scale Amazon Reviews dataset, collected in 2023 by McAuley Lab, and it includes rich features such as:
- User Reviews (ratings, text, helpfulness votes, etc.);
- Item Metadata (descriptions, price, raw image, etc.);
- Links (user-item / bought together graphs).
What's New?
In the Amazon Reviews'23, we provide:
- Larger Dataset: We collected 571.54M reviews, 245.2% larger than the last version;
- Newer Interactions: Current interactions range from May. 1996 to Sep. 2023;
- Richer Metadata: More descriptive features in item metadata;
- Fine-grained Timestamp: Interaction timestamp at the second or finer level;
- Cleaner Processing: Cleaner item metadata than previous versions;
- Standard Splitting: Standard data splits to encourage RecSys benchmarking.
Basic Statistics
We define the #R_Tokens as the number of tokens in user reviews and #M_Tokens as the number of tokens if treating the dictionaries of item attributes as strings. We emphasize them as important statistics in the era of LLMs.
We count the number of items based on user reviews rather than item metadata files. Note that some items lack metadata.
Compared to Previous Versions
| Year | #Review | #User | #Item | #R_Token | #M_Token | #Domain | Timespan |
|---|---|---|---|---|---|---|---|
| 2013 | 34.69M | 6.64M | 2.44M | 5.91B | -- | 28 | Jun'96 - Mar'13 |
| 2014 | 82.83M | 21.13M | 9.86M | 9.16B | 4.14B | 24 | May'96 - Jul'14 |
| 2018 | 233.10M | 43.53M | 15.17M | 15.73B | 7.99B | 29 | May'96 - Oct'18 |
| 2023 | 571.54M | 54.51M | 48.19M | 30.14B | 30.78B | 33 | May'96 - Sep'23 |
Grouped by Category
| Category | #User | #Item | #Rating | #R_Token | #M_Token | Download |
|---|---|---|---|---|---|---|
| All_Beauty | 632.0K | 112.6K | 701.5K | 31.6M | 74.1M | review, meta |
| Amazon_Fashion | 2.0M | 825.9K | 2.5M | 94.9M | 510.5M | review, meta |
| Appliances | 1.8M | 94.3K | 2.1M | 92.8M | 95.3M | review, meta |
| Arts_Crafts_and_Sewing | 4.6M | 801.3K | 9.0M | 350.0M | 695.4M | review, meta |
| Automotive | 8.0M | 2.0M | 20.0M | 824.9M | 1.7B | review, meta |
| Baby_Products | 3.4M | 217.7K | 6.0M | 323.3M | 218.6M | review, meta |
| Beauty_and_Personal_Care | 11.3M | 1.0M | 23.9M | 1.1B | 913.7M | review, meta |
| Books | 10.3M | 4.4M | 29.5M | 2.9B | 3.7B | review, meta |
| CDs_and_Vinyl | 1.8M | 701.7K | 4.8M | 514.8M | 287.5M | review, meta |
| Cell_Phones_and_Accessories | 11.6M | 1.3M | 20.8M | 935.4M | 1.3B | review, meta |
| Clothing_Shoes_and_Jewelry | 22.6M | 7.2M | 66.0M | 2.6B | 5.9B | review, meta |
| Digital_Music | 101.0K | 70.5K | 130.4K | 11.4M | 22.3M | review, meta |
| Electronics | 18.3M | 1.6M | 43.9M | 2.7B | 1.7B | review, meta |
| Gift_Cards | 132.7K | 1.1K | 152.4K | 3.6M | 630.0K | review, meta |
| Grocery_and_Gourmet_Food | 7.0M | 603.2K | 14.3M | 579.5M | 462.8M | review, meta |
| Handmade_Products | 586.6K | 164.7K | 664.2K | 23.3M | 125.8M | review, meta |
| Health_and_Household | 12.5M | 797.4K | 25.6M | 1.2B | 787.2M | review, meta |
| Health_and_Personal_Care | 461.7K | 60.3K | 494.1K | 23.9M | 40.3M | review, meta |
| Home_and_Kitchen | 23.2M | 3.7M | 67.4M | 3.1B | 3.8B | review, meta |
| Industrial_and_Scientific | 3.4M | 427.5K | 5.2M | 235.2M | 363.1M | review, meta |
| Kindle_Store | 5.6M | 1.6M | 25.6M | 2.2B | 1.7B | review, meta |
| Magazine_Subscriptions | 60.1K | 3.4K | 71.5K | 3.8M | 1.3M | review, meta |
| Movies_and_TV | 6.5M | 747.8K | 17.3M | 1.0B | 415.5M | review, meta |
| Musical_Instruments | 1.8M | 213.6K | 3.0M | 182.2M | 200.1M | review, meta |
| Office_Products | 7.6M | 710.4K | 12.8M | 574.7M | 682.8M | review, meta |
| Patio_Lawn_and_Garden | 8.6M | 851.7K | 16.5M | 781.3M | 875.1M | review, meta |
| Pet_Supplies | 7.8M | 492.7K | 16.8M | 905.9M | 511.0M | review, meta |
| Software | 2.6M | 89.2K | 4.9M | 179.4M | 67.1M | review, meta |
| Sports_and_Outdoors | 10.3M | 1.6M | 19.6M | 986.2M | 1.3B | review, meta |
| Subscription_Boxes | 15.2K | 641 | 16.2K | 1.0M | 447.0K | review, meta |
| Tools_and_Home_Improvement | 12.2M | 1.5M | 27.0M | 1.3B | 1.5B | review, meta |
| Toys_and_Games | 8.1M | 890.7K | 16.3M | 707.9M | 848.3M | review, meta |
| Video_Games | 2.8M | 137.2K | 4.6M | 347.9M | 137.3M | review, meta |
| Unknown | 23.1M | 13.2M | 63.8M | 3.3B | 232.8M | review, meta |
Check Pure ID files and corresponding data splitting strategies in Common Data Processing section.
Quick Start
Load User Reviews
from datasets import load_dataset
dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_review_All_Beauty", trust_remote_code=True)
print(dataset["full"][0])
{'rating': 5.0,
'title': 'Such a lovely scent but not overpowering.',
'text': "This spray is really nice. It smells really good, goes on really fine, and does the trick. I will say it feels like you need a lot of it though to get the texture I want. I have a lot of hair, medium thickness. I am comparing to other brands with yucky chemicals so I'm gonna stick with this. Try it!",
'images': [],
'asin': 'B00YQ6X8EO',
'parent_asin': 'B00YQ6X8EO',
'user_id': 'AGKHLEW2SOWHNMFQIJGBECAF7INQ',
'timestamp': 1588687728923,
'helpful_vote': 0,
'verified_purchase': True}
Load Item Metadata
dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_meta_All_Beauty", split="full", trust_remote_code=True)
print(dataset[0])
{'main_category': 'All Beauty',
'title': 'Howard LC0008 Leather Conditioner, 8-Ounce (4-Pack)',
'average_rating': 4.8,
'rating_number': 10,
'features': [],
'description': [],
'price': 'None',
'images': {'hi_res': [None,
'https://m.media-amazon.com/images/I/71i77AuI9xL._SL1500_.jpg'],
'large': ['https://m.media-amazon.com/images/I/41qfjSfqNyL.jpg',
'https://m.media-amazon.com/images/I/41w2yznfuZL.jpg'],
'thumb': ['https://m.media-amazon.com/images/I/41qfjSfqNyL._SS40_.jpg',
'https://m.media-amazon.com/images/I/41w2yznfuZL._SS40_.jpg'],
'variant': ['MAIN', 'PT01']},
'videos': {'title': [], 'url': [], 'user_id': []},
'store': 'Howard Products',
'categories': [],
'details': '{"Package Dimensions": "7.1 x 5.5 x 3 inches; 2.38 Pounds", "UPC": "617390882781"}',
'parent_asin': 'B01CUPMQZE',
'bought_together': None,
'subtitle': None,
'author': None}
Check data loading examples and Huggingface datasets APIs in Common Data Loading section.
Data Fields
For User Reviews
| Field | Type | Explanation |
|---|---|---|
| rating | float | Rating of the product (from 1.0 to 5.0). |
| title | str | Title of the user review. |
| text | str | Text body of the user review. |
| images | list | Images that users post after they have received the product. Each image has different sizes (small, medium, large), represented by the small_image_url, medium_image_url, and large_image_url respectively. |
| asin | str | ID of the product. |
| parent_asin | str | Parent ID of the product. Note: Products with different colors, styles, sizes usually belong to the same parent ID. The “asin” in previous Amazon datasets is actually parent ID. Please use parent ID to find product meta. |
| user_id | str | ID of the reviewer |
| timestamp | int | Time of the review (unix time) |
| verified_purchase | bool | User purchase verification |
| helpful_vote | int | Helpful votes of the review |
For Item Metadata
| Field | Type | Explanation |
|---|---|---|
| main_category | str | Main category (i.e., domain) of the product. |
| title | str | Name of the product. |
| average_rating | float | Rating of the product shown on the product page. |
| rating_number | int | Number of ratings in the product. |
| features | list | Bullet-point format features of the product. |
| description | list | Description of the product. |
| price | float | Price in US dollars (at time of crawling). |
| images | list | Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image. |
| videos | list | Videos of the product including title and url. |
| store | str | Store name of the product. |
| categories | list | Hierarchical categories of the product. |
| details | dict | Product details, including materials, brand, sizes, etc. |
| parent_asin | str | Parent ID of the product. |
| bought_together | list | Recommended bundles from the websites. |
Citation
@article{hou2024bridging,
title={Bridging Language and Items for Retrieval and Recommendation},
author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian},
journal={arXiv preprint arXiv:2403.03952},
year={2024}
}
Contact Us
Report Bugs: To report bugs in the dataset, please file an issue on our GitHub.
Others: For research collaborations or other questions, please email yphou AT ucsd.edu.