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metadata
task_categories:
  - text-classification
  - feature-extraction
  - sentence-similarity
  - text2text-generation
  - translation
language:
  - en
tags:
  - e-commerce
  - products
  - amazon
  - arabic
size_categories:
  - 100K<n<1M

Dataset Card for Amazon Products 2023 Arabic

Dataset Summary

This dataset contains product metadata from Amazon, filtered to include only products that became available in 2023. The dataset is intended for use in semantic search applications and includes a variety of product categories.

  • Number of Rows: 117,243
  • Number of Columns: 17

Data Source

The data is sourced from Amazon Reviews 2023. It includes product information across multiple categories, with additional embeddings.

NLLB 1.3B was used for translation to Modern Standard Arabic.

Embeddings were created from the title_arb + description_arb using the text-embedding-3-small model.

Dataset Structure

Number of Products by Filename

filename product_count
0 meta_Amazon_Fashion 470
1 meta_Appliances 573
2 meta_Arts_Crafts_and_Sewing 2948
3 meta_Automotive 7161
4 meta_Baby_Products 526
5 meta_Beauty_and_Personal_Care 1402
6 meta_Books 2
7 meta_CDs_and_Vinyl 1319
8 meta_Cell_Phones_and_Accessories 5062
9 meta_Clothing_Shoes_and_Jewelry 41777
10 meta_Digital_Music 56
11 meta_Electronics 7681
12 meta_Gift_Cards 8
13 meta_Grocery_and_Gourmet_Food 96
14 meta_Handmade_Products 1018
15 meta_Health_and_Household 4760
16 meta_Health_and_Personal_Care 93
17 meta_Home_and_Kitchen 17326
18 meta_Industrial_and_Scientific 1216
19 meta_Magazine_Subscriptions 3
20 meta_Musical_Instruments 639
21 meta_Office_Products 3545
22 meta_Patio_Lawn_and_Garden 3075
23 meta_Pet_Supplies 2742
24 meta_Software 157
25 meta_Sports_and_Outdoors 6343
26 meta_Tools_and_Home_Improvement 4776
27 meta_Toys_and_Games 1367
28 meta_Unknown 541
29 meta_Video_Games 561

Columns

  • parent_asin (str): Unique identifier for the product.
  • date_first_available (datetime64[ns]): The date when the product first became available.
  • title (str): Title of the product.
  • title_arb (str): Title of the product translated to Modern Standard Arabic.
  • description (str): Description of the product.
  • description_arb (str): Description of the product translated to Modern Standard Arabic.
  • filename (str): Filename associated with the product metadata.
  • main_category (str): Main category of the product.
  • categories (List[str]): Subcategories of the product.
  • store (str): Store information for the product.
  • average_rating (float64): Average rating of the product.
  • rating_number (float64): Number of ratings for the product.
  • price (float64): Price of the product.
  • features (List[str]): Features of the product.
  • details (str): Additional details of the product. The string is JSON serializable.
  • embeddings (List[float64]): Embeddings generated for the product using text-embedding-3-small model.
  • image (str): URL of the product image.

Missing Values

  • main_category: 24,805 missing values
  • store: 253 missing values
  • rating_number: 6 missing values
  • price: 35,869 missing values

Sample Data

[
  {
    "parent_asin": "B000044U2O",
    "date_first_available": "2023-04-29T00:00:00",
    "title": "Anomie & Bonhomie",
    "description": "Amazon.com Fans of Scritti Politti's synth-pop-funk masterpiece Cupid & Psyche 85 may be shocked by how far afield Scritti mastermind Green Gartside has gone since then. Anomie & Bonhomie, his return to recording after a decadelong absence, ranges from guest shots by rappers and funksters such as Mos Def and Me'Shell Ndegeocello to Foo Fighters tributes. Gartside's trademark breathy vocals and spot-on melodicism do find their places here, but are often forced to make way for other influences. Neither a total success nor a total failure, Anomie does display a spark that makes one hope that Gartside doesn't wait so long to record again. --Rickey Wright",
    "filename": "meta_Digital_Music",
    "main_category": "Digital Music",
    "categories": [],
    "store": "Scritti Politti Format: Audio CD",
    "average_rating": 4.2,
    "rating_number": 56.0,
    "price": null,
    "features": [],
    "details": "{'Date First Available': 'April 29, 2023'}",
    "embeddings": [],
    "image": "https://m.media-amazon.com/images/I/41T618NE88L.jpg"
  },
  ...
]

Usage

This dataset can be used for various applications, including:

  • Semantic Search: Utilizing the embeddings to find similar products based on textual descriptions.
  • Product Recommendation: Enhancing recommendation systems with detailed product metadata.

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

For questions or issues regarding the dataset, please contact Amazon Reviews 2023.